U N I V E R S I T Y O F C O P E N H A G E N F A C U L T Y O F H U M A N I T I E S

Master Thesis Frida Louise Irhøj Damhus

Minding the Gap A Study of Algorithms as Rhetorical Constructs and the

Knowledge Gaps That Surround Them.

29.01.2016

Institutnavn: Institut for Medier, Erkendelse og Formidling Afdeling: Afdeling for Retorik Forfatter: Frida Louise Irhøj Damhus Titel og evt. undertitel: Minding the Gap: A Study of Algorithms as Rhetorical Constructs and

the Knowledge Gaps That Surround Them. Vejleder: Rasmus Rønlev Afleveret den: 29. Januar 2016 Antal tegn: 191.892 Antal normalsider: 79,9 Omregning: 1 ns = 2400 anslag

Billedkreditering: Launchable Magazine, 3. April 2015, hentet fra

http://www.launchablemag.com/assets/images/upload/Facebook45.jpg

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Resumé Dette speciale beskæftiger sig med en retorisk definition af algoritmer og spørger, hvordan vi

teoretisk og praktisk kan nærme os algoritmer fra et retorisk udgangspunkt. Med udgangspunkt i

teori af retoriker Aaron Hess defineres algoritmer indledningsvist som retoriske ud fra teoretiske

overvejelser om deres indbyggede kapacitet for at fremme Burkeansk identifikation, påvirke

retorisk agency og fungere persuasivt.

I forlængelse af den teoretiske diskussion af algoritmer, introduceres begrebet knowledge gaps for

at italesætte den vidensmæssige afstand, der antageligvis eksisterer i samfundet generelt om

algoritmers stadig større rolle i vores online-liv. Som et praktisk eksempel på både algoritmers

indflydelse og eksistensen af knowledge gaps, analyseres en case fra 2014, hvor Facebook

offentliggjorde et studie, der utvetydigt fastslog, hvordan algoritmen, der styrer brugernes news

feed, kan bruges til emotionel manipulation. Tre hovedgrupper af reaktioner på offentliggørelsen

udsættes for en pentadisk analyse, der har til formål at kortlægge de forskellige konstruktioner af

situationens elementer, som de er til stede i artefakterne. De tre grupper består af Facebook,

Facebookbrugere og endelig teknologikyndige udenforstående i form af en blogger og en journalist.

Ultimativt har den teoretiske gennemgang og den pentadiske analyse til formål at lede diskussionen

i specialet hen på de mulige problematikker knowledge gaps og algoritmiske medier har for

udøvelsen af retorisk medborgerskab i 2016. I dette speciale argumenteres der for, at algoritmer er

en af de mest signifikante og samtidig mindst åbenlyse former for persuasio, der udøves i dag.

Netop den dikotomi gør algoritmer vigtige at beskæftige sig med fra et retorisk udgangspunkt, da

retorikken kan adressere algoritmers funktioner som faciliterende for én

kommunikationsvirkelighed frem for en anden. På den måde er nærværende speciale et eksempel

på, hvordan retorikere kan tilgå et emnefelt, der på én gang ligger i ydergrænsen af fagets klassiske

domæne og samtidig midt i dets moderne relevans og anvendelighed.

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1.0 Introduction “Do they choose what they think is the

best for me to see? Based on what?”

- Participant P37 reacting to the news

of an algorithm sorting his FB News

Feed (Eslami et al. 2015).

It was not until recently that I became aware of the extent to which algorithms impact our daily

lives as they, ever increasingly so, become digitalized. Of course I noticed the targeted ads present

on the variety of platforms I frequent. I have always been aware that the data I present businesses

with when I click, purchase something, or leave a site is valuable and tradeable. I was, however,

unaware of how human the underlying current of the technological instalments in place to perform

these tasks are. I was unaware of how rhetorically significant they are.

To write a thesis on algorithms without a background in computer science, coding, or programming

in any shape or form might appear odd at first. What business does a rhetorician have in the

machine room? The truth is: Not much - but some. It is not in the depths of equations and coded

command structures that our immediate strengths lie, but, as this thesis is meant to prove, we have

the ability to assess concepts such as algorithms in different and meaningful ways. Through a

rhetorical lens, algorithms change. Suddenly we can appreciate them as more than code. They

become the results they help us find, the exchanges they facilitate, and the imprint they leave on

behaviour. Importantly, they also become assumptions: The lines of reasoning behind

recommending one book after you have purchased another, or showing you a new restaurant review

following your most recent night out, are based on our assumptions about each other. Simplified

here but developed on later, it could look something like “Likeness is good”. And as such,

algorithms become rhetorical – persuasive, agency-affecting, identification-facilitating. They are all

of those things, and more.

My work with this thesis started out as a passion project trying to understand the role algorithms

play in our lives. I was impressed by how little I knew about something so omnipresent and

impactful as I continued to educate myself on the matter. I ascribed it to their simultaneous

imperceptible nature – they work in the backdrop of things, like the subconscious to our minds.

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Like rhetorician Aaron Hess, whose enthusiastic and at times perplexing endeavours into the

combination of rhetoric and code I admire and in part emulate, I have come to see that this

imperceptibility is to be considered a trait of algorithms. As another algorithm-aficionado, Fenwick

McKelvey, puts it almost poetically: “This control (i.e. algorithms) occurs deep within opaque

technical systems far from the political attention capable of addressing its influence.” (McKelvey

2014, p. 597). It is this political and in my interpretation rhetorical attention I entered into the work

wanting to grant algorithms.

And, as it turned out, I was not the only one unaware of the role algorithms play in our online lives.

Researching the matter, it quickly became apparent that the (mis)management of algorithms have

caused several public controversies that prove the very palpable social consequences of concepts we

could have otherwise dismissed as “too-hard-to-comprehend” technology. As an example of such a

controversy, one researcher, Mike Ananny, wondered why the Google Play Store would show

people downloading the gay dating app Grindr a recommendation for also downloading a Sex

Offender Search application (Ananny 2011). This caused uproar and inquiry into the underlying

assumptions present in the recommendations provided through the algorithms – namely that being

homosexual in some way could be linked to being a sex offender. In this light, for a rhetorician to

avoid getting familiar with algorithms is, to me, to miss out on one of the subtlest and most

widespread ways people are now being persuaded to act on and identify with the world around

them.

One case caught my attention in a different way as it connected academia, algorithms, and public

controversy. It concerned Facebook (hereafter FB), an absolute social media behemoth, and a

particular piece of research published in their name back in 2014. As an overview of the

background and a run-through of the case will show, the publication of the research created a public

controversy posing a significant face-threatening situation for FB. The controversy also made

evident how little a majority of people knew about the workings of one of the most frequented

platforms in the world – especially when it came to the presence and management of algorithms. It

allowed me to assess, on limited grounds of course, the current state of public awareness of

algorithms, but also the ways in which occurrences like that of 2014 are explained by FB itself, and,

as a contrast, by independent, technologically savvy outsiders to it all. In other words, this particular

case granted insight into a moment in time where the role algorithms play online was made

painstakingly clear to a lot of people otherwise unaware of their existence. The resulting

controversy, involving academics, members from the tech-community, FB officials and last but not

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least FB’s users, reveal the extent to which we as a pan-Western society are in need of educational

efforts towards the average Internet user. Not only for the sake of the individual in making informed

decisions for themselves, but also for the sake of preserving or even improving the quality of our

societal co-existence. The obvious concern this raises for a rhetorician is the impact our awareness

of algorithms has on the enactment of rhetorical citizenship today. These statements might appear

grand – I aim to prove their points in the thesis that follows.

On a final note, the references in this thesis follow a certain order, given their character. References

to theory and direct quotes figure in-text, whereas meta-comments and minor explanatory passages

will be found in footnotes on the relevant pages. In the analysis, the artefact consisting of a

commentary track requires longer and more specific references for each comment included.

Therefore, these references will be found as endnotes. The difference is accentuated in the use of

Arabic numbers for footnotes, and Roman numbers for endnotes. This thesis adapts APA-style

referencing.

1.1 Background In June 2015, FB had an average of 968 million daily active users, and 844 million daily active

mobile users; the vast majority of which came from outside the United States and Canada (FB

2015). Overall, when it comes to social media, FB is at the top of the game – not only in terms of

user base, but also profitability and market share (Gerber 2014). The self-proclaimed mission of FB

is to “give people the power to share”, and to help them “stay connected with friends and family

(...) and to share and express what matters to them” (FB 2015).

One of the key features of the interface FB provides its users with is the FB News Feed1 – and it

appears to accomplish several of the tasks in the company’s mission statement mentioned above.

The News Feed acts as landing page once a user logs onto the platform, thus providing a point of

entry to the service – a kind of front page to the individual user’s FB account. Any given News

Feed is compiled of what would appear to be random mix of status updates from friends, clips from

popular media, commercials, posts others have liked, links others have shared and pictures people

have been tagged in. It acts as a sort of forum, where users become animated to each other as their

1 The News Feed algorithm is also known as ‘EdgeRank’. For the purpose of consistency, and since it hints at the function of the algorithm, I have chosen to stick with ‘News Feed’. For a more in-detail explanation and a qualified estimate of its technological properties, see Jason Kincaid’s (2010) “EdgeRank: The Secret Sauce that Makes FB’s News Feed Tick,”.

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activities on the platform are documented and displayed for all to see, comment on and, of course,

‘like’ and ‘share’. Being a list that you can scroll through, News Feed consists of posts that are at

the top and thus spatially prioritized over other posts, since a user will encounter them first – and

this prioritization caught my interest. Is it random what ends up at the top? And if not: Who

decides?

FB itself sparingly describes News Feed as “a constantly updating list of stories”, and reveals, “the

order of stories in your News Feed is influenced” by a number of signifiers, such as who posted the

story, and what number of likes it has received (FB n.d.). They add: “This helps you to see the most

interesting stories from the friends you interact with the most” (Ibid). The vagueness and

passiveness of the statement caught my eye when I first read it: Something is helping us to see the

most interesting things from the people we are connected to the most. The predetermined values

underlying this message appear numerous. A question seemed to emerge from behind the others:

How is this apparent sorting of content carried out? Who is helping us?

1.2 What News Feed feeds us It seems almost ironic that a service so passively described by FB simultaneously carries the name

News Feed. The ‘News’ part of the name, however, is not entirely misleading. Today, the Pew

Research Center estimates that 63 % of FB users get news from the site, a significant increase

compared to 47 % recorded in 2013 (Barthel et al. 2015). Increasingly, people rely on FB for news,

and the place to get it is the News Feed. The importance of how, what, and by whom information is

presented to us, then, would seem to increase as rising numbers turn to FB for updates on the

outside world. However it appears that the more ingrained media types become in our routines and

the more readily we turn to them, the more seamless and integrated the usage becomes – and the

less scrutiny we, as individuals, give it. This observation is supported by Harvard researchers and

psychologists Daniel M. Wegner and Adrian F. Ward, who in “How Google Is Changing Your

Brain” (2013) explain how we increasingly “incorporate the Internet into a subjective sense of self”

(Wegner & Ward 2013, p. 53). Through their research, Wegner and Ward found that instead of

perceiving services on the Internet as external measures that we have at our disposal, people now

have “the sense that the Internet has become a part of their own cognitive tool set” (Ibid.). Even

when participants in a study accomplished a task by knowingly using an Internet service, such as

Google, cognitive self-esteem rose as a result (Ibid.). Wegner and Ward coin the term “Intermind”

to describe the integration of Internet and human mind, while noting the irony of it all: “The advent

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of the “information age” seems to have created a generation of people who feel they know more

than ever before – when their reliance on the Internet means that they may know ever less about the

world around them” (2013, p. 53). So if FB become to us socially what Google is becoming to us

cognitively2, the ‘Feed’ part of News Feed might not be misleading after all.

1.3 Addressing the elephant: Algorithms They might not be at the forefront of public awareness, or even in the vicinity of it, but algorithms

are essentially the answer to all the questions I have posed so far. They account for an immense and

completely indispensable part of the Internet services we frequent the most: Google – and really all

other search engines –, FB, and Twitter. They are what make the wheels go round: They fill our

News Feeds, rank our trends and sort our search results. They work seamlessly, leaving little sign of

themselves as they sort, classify, recommend, update, prioritize, systemize and introduce data to us.

So invisible are they in everyday Internet use, that FB, as mentioned earlier, does not even use the

word “algorithm” in their answer to the question “What is News Feed?” in their Help section. What

could have been added to the otherwise vague description: The FB News Feed is algorithmic – and

profitable. The personalized streams of content on News Feed “has turned FB into an advertising

behemoth that generated $12.5 billion in revenue in 2014” (Luckerson 2015). At the same time,

recent user studies find that over half of the people who use FB regularly are completely unaware of

the fact that News Feed is an algorithm that sorts the information they are shown (Eslami et al.

2015). Why does all this matter? It matters because, as Tarleton Gillespie, Professor of

Communication at Cornell University and Principal Research at Microsoft Research, puts it:

Algorithms (...) provide a means (...) to participate in social and political discourse, and to familiarize ourselves with the publics in which we participate. They are now a key logic governing the flows of information on which we depend with the “power to enable and assign meaningfulness, managing how information is perceived by users, the ‘distribution of the sensible’”3

To define them simply, "...any sequence of instructions that can be obeyed by a robot, is called an

algorithm" and algorithms as such are essential command structures in the workings of our

digitalized, computerized society (Stone 1972, p. 4). Their omnipresence in mind, my quest is not

one to criminalize algorithms as a concept – this would be a futile and meaningless struggle against

what is and what must be. Concurring with rhetorician Aaron Hess, “rather than abandoning digital

2 This is not a completely far-fetched comparison, as The Time Magazine reports how “American users spend nearly as much time on FB per day (39 minutes) as they do socializing with people face-to-face (43 minutes)” (Luckerson 2015). 3 Gillespie 2014.

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devices,” I hold that “users should be attentive to the ways that digital cookies and algorithms affect

our ideas, our desires, and our selves” (2014, p. 18). It is algorithms’ role in places such as the FB

News Feed that draw critical attention. Critical attention that rhetorician Barbara Warnick labelled

over a decade ago: “programming and automation (...) should be taken into account by critics

interested in how content is adapted to appeal to audience interests and needs”, as she urged

rhetorical critics not to be too “printcentric” (Warnick 2005, p. 330). Following Gillespie, the

importance of understanding what we deal with on a daily basis when encountering algorithms

becomes apparent. If algorithms are influential enough to affect our ways of participating in social

and political discourse, to manage how information is perceived by users, and to somewhat govern

the way in which we affiliate ourselves with publics, then they are indeed items worthy of rhetorical

scrutiny. Combined with their seemingly invisible presence, and given that a “user’s perceived

knowledge about an algorithm can affect their behaviour” (Eslami et al. 2015), algorithms seem to

become all the more intriguing – and rhetorically relevant.

1.3.1 Why not cookies?

On a short note, I want to make clear the distinction I make between cookies and algorithms, and

why I do not provide further definition of or attention to cookies. This decision is based on the

difference that cookies collect information, while algorithms sort and process it4. They are both

essential to each other’s workings, but the algorithm carries the underlying assumptions and

functions that are, in my view alongside others’ (Eslami et al. 2015; Gillespie 2014; Hess 2014;

McKelvey 2014) more interesting. While cookies will be mentioned sporadically throughout the

thesis, no further introduction to their technological properties will be given5. Sufficient to say is

that they are an absolutely essential but in this context less rhetorically significant component of our

online lives.

1.4 The case in question A particular case links the so far introduced components of FB and its News Feed, algorithms and

their simultaneous opaqueness and importance for life online. Back in 2012, FB conducted a study

involving almost 700,000 FB users. The users were unaware of the experiment being conducted,

4 A definition of cookies provided by Google: “a small file containing a string of characters that is sent to your computer when you visit a Website. We use cookies to improve the quality of our service and to better understand how people interact with us. Google does this by storing user preferences in cookies and by tracking user trends and patterns of how people search” (“Google Privacy Center” 2005). 5 For a more in-depth look at cookies, see Aaron Hess’ “Reconsidering the Rhizome” (2008, p. 45).

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and the activities involved were not revealed until the publishing of the study in 2014. The title,

“Experimental evidence of massive-scale emotional contagion through social networks”, contains

the key term ‘emotional contagion’ which was what researchers Adam Kramer, Jamie Guillory and

Jeffrey Hancock set out to investigate the existence of (Kramer, Guillory & Hancock 2014). By

altering the contents of users’ News Feeds, the researchers reached a significant and also somewhat

troubling result: “emotional states can be transferred to others via emotional contagion [via the

News Feed], leading people to experience the same emotions without their awareness” (Ibid.).

Content was altered to be less positive in one group, and less negative in another, in order to detect

whether these changed conditions would produce an increase in similar posts as a reaction (Ibid.).

The study found that users responded by producing content that corresponded with the ‘less

positive/less negative’ new emotional environment they were presented with in their News Feed

(Ibid.).

The publication of the study caused a massive public backlash. Several international news outlets

and professional as well as private blogs awarded the study top placement as it started to spark

attention the weekend of June 27-29, 2014 (ABC News 2014; BBC News 2014; Goel 2014; Meyer

2014; Penn 2014; Schaefer 2014). Alongside the creation of a dedicated Twitter-hashtag,

#FBExperiment6, it quickly proved to be more than a passing matter, with headlines such as “FB

Tinkers With Users’ Emotions”, and “FB's Secret Mood Manipulation Experiment” (Goel 2014;

Robinson 2014). Even today, debates are still active, with some writers attributing what they see as

the demise of democratic values such as freedom of speech to the algorithmic constructions of FB

and its likes (Smithson 2015). In comparison, less than two years prior to the publication of the FB

study, a different experimental study involving 61 million people was completely bypassed in terms

of public attention (Bond et al. 2012). Perhaps we can attribute this to FB’s uniqueness, being as

large, profitable and influential as it is, and the conditions surrounding our (perceived) free social

life on the platform that became highlighted as a result of the study. The uproar, however, could

also be interpreted to be another expression of the general unawareness that exists surrounding

platforms such as FB. What is important to note from the get-go is that manipulating or otherwise

managing the News Feed is something that occurs constantly in the day-to-day running of FB. This

has, since the whole incident back in 2014, been publicly stated numerous times by the FB

researchers themselves. As one of them, Jeff Hancock, put it in a subsequent panel debate on ethics

6 https://twitter.com/hashtag/FBexperiment visited September 8, 2015.

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in large scale social experiments: “I’m not sure whether this means we need to bring in an education

component to help people understand that their news feeds are altered all the time by FB?”

(Hancock 2014). The general reaction to the publication of the study would seem to suggest so.

Despite media coverage and criticism, there were no immediate legal grounds for complaint, since

FB through its Terms and Conditions had secured rights to perform studies without seeking any

further permission from its user base7. However, avoiding legal action did not save FB from the

backlash that followed as users became aware of the character of the study and their unknowing

partaking in it. Presumably, the affair made a number of things evident to FB users: 1) That there is

an algorithm that can alter the news, updates and information being shown to them, 2) that someone

is in control of that algorithm, and 3) that the design of the personalized streams of content that is

the News Feed matters, since it has the ability to alter psychological states and affect the discourse

we produce as a result. And these realizations, or variations of them, produced heated debates

among FB users – concerning power, publics and privacy.

7 It has later been debated whether or not FB added a term regarding research after the beginning of the study (Smithson 2015). There has also been criticism of the lack of ethical considerations – besides the legal considerations – and it has been argued that clicking ‘Agree’ to a Terms and Conditions page should not equal informed consent on studies such as Kramer, Guillory and Hancock’s (2014) (Penn, 2014).

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2.0 Problem Definition

2.1 Problem formulation With this thesis I argue that rhetorical scholars and practitioners should consider algorithms, the

technological backdrop that shapes our user experiences on major online platforms such as FB, as

rhetorical entities with persuasive properties. I argue this first theoretically, through a review of the

existing literature on the subject, and then practically, through an analysis of various responses to

the already introduced FB experiment. I show how differently relevant groupings around the case

reacted to it, revealing varying levels of understanding of the role algorithms play on a site such as

FB and online in general. These groupings are identified to be the authors of the study, corporate

FB, the users, and finally the tech-community. Third and finally, in the discussion following the

analysis, I link the findings of the two previous parts to the greater concerns relevant to algorithms

and their persuasive qualities, and the discrepancy between the amount of people being influenced

by algorithms and the amount of people aware of it. I link this to a discussion of political

polarization and rhetorical citizenship, and their respective links to the digitalization of our

societies. Ultimately I believe that a rhetorical definition of algorithms make them more accessible

concepts to the average user of the Internet and therefore has a double-sided utility: 1) It presents

practitioners of rhetoric with a new field of investigation, and 2) It presents publics with an

explanation as to what algorithms do. Overall, this thesis answers the question:

How can we theoretically and practically approach algorithms from the point of rhetoric, and what

contributing points to the wider society can we observe from such an exploration?

The work in the different parts of the thesis, as described above, can be summarized in three sub-

questions each answering a part of the overall question:

• Part I: How can algorithms be defined rhetorically, following existing literature on the

matter?

• Part II: What characterized the rhetorical responses to the FB case of 2014, where the

algorithmic power inherent to the site was made evident to the public at large?

• Part III: What concerns do the concept of ‘knowledge gaps’ between providers and users of

algorithmic media such as FB present us with?

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2.1.1 Part I: Theory In the first part of this thesis, I establish algorithms as constructs imbued with significant rhetorical

power. To do so, I incorporate and discuss literature from an array of academic fields. Before

treating algorithms in particular, I go over the difference between customization and

personalization, and the significant rhetorical implications of the latter, following, among others,

Shyam Sundar and Sampada Marathe’s findings in “Personalization versus Customization: The

Importance of Agency, Privacy, and Power Usage” (2010). Moving towards a further definition of

algorithms as imbued with rhetorical power, a key theorist I employ is Professor of Communication

Aaron Hess, who has treated algorithms throughout his academic work (2008; 2009; 2014). Hess

offers, borrowing from Burkean rhetoric, the concept of digital rhetorical identification to explain

“digital technology and its effect on the unconscious, argumentation, and public deliberation”

(2014, p. 1). Thus Hess provides an offset for further discussion of how our rhetorical practice alters

as our communicative environments become digitalized. The aim of the first part of the thesis is to

approach algorithms theoretically and map out their rhetorical significance as powerful influencers

of identification, agency and persuasion.

2.1.2 Part II: Case analysis The second part of this thesis analyses an actual instance where the existence of algorithms became

evident to the vast mass of everyday FB users. In order to answer an overarching question of the

rhetorical role of algorithms in society today, I analyse four different responses to the publication of

the FB experiment. For each response, I carry out a pentadic analysis following Kenneth Burke’s

instructions in A Grammar of Motives (1969a), in order to illustrate how each of the responses

construct the conflict discursively. First, I analyse an entry from the FB head office and a post made

by one of the researchers, Adam Kramer, on his FB-page following the publication of the study.

Second, entries in the commentary field of Kramer’s post, where FB users voice their opinions are

analysed. Finally, I analyse responses from two different external writers, interpreted to inhabit the

role of knowledge-privileged outsiders: A blog and an entry to MIT’s technology review. In

choosing and limiting the online artefacts I adhere to the view of Michael Calvin McGee, who

posits discourse to consist of fragments of which the rhetorical critic must “[invent] a text suitable

for criticism” (1990, p. 288). Elisabeth Hoff-Clausen (2008) seconds this approach, and her

methodological recommendations for composing particularly online artefacts suitable for analysis

will be introduced in greater detail before the analysis of the artefacts.

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2.1.3 Part III: Discussion The third and final part of the thesis ties together the observations already made in the theoretical

examination of the concept of algorithms and the case analysis. Part III discusses the wider

implications of varying levels of awareness of concepts such as algorithms, and treats the notion of

a knowledge gap existing between providers and users of algorithmic media such as FB. As such,

the discussion lifts the question of algorithms into a general consideration of how we, as a society,

should consider the increasing presence of algorithms in our daily online interactions. As an

extension of the theory and the findings of the analysis of the FB case, Part III discusses the way in

which algorithmic media can be said to influence and eventually limit the degree to which the

average user of Internet products such as the FB News Feed can enact rhetorical citizenship – on

and offline.

2.2 Aim and purpose In the overall considerations of the aim and purpose of this thesis I subscribe to the sentiments of

Barry Brummett as presented in “Rhetorical Theory As Heuristic and Moral: A Pedagogical

Justification” (1984). Like Brummett, I consider the nature and role of rhetorical theory and

criticism to be a heuristic and moral one, and thus regard “rhetorical theory and criticism’s ultimate

goal and justification” to be “pedagogical: to teach people how to experience their rhetorical

environments more richly” (1984, p. 103). Furthermore I believe that by performing criticism in

accordance with Brummett’s overall principles, we can approach the question, as reiterated by

Barbara Warnick, of “how to connect discursive practices with moral judgment” (Warnick 1998, p.

74).

Rhetorical theory and criticism is heuristic and moral because it forms a “device that helps us learn

about the world” as it “expands one’s ability to assemble message sets consciously and to

understand rhetorical transactions on several levels at once” (Brummett 1984, p. 103). Developing

on Samuel Becker’s8 theory of audience perception in mass media cultures, Brummett further

describes how, in order to make sense of the world, we create ‘message sets’ (1984, p. 101). If we

do so without being “trained to be focally aware” of how we do so, we create message sets

“uncritically, perhaps even unconsciously”, resulting in a particular world view (Brummett 1984, p.

103-104). I believe the publication of the FB experiment awoke a large number of FB users to a

8 In The Prospect of Rhetoric, eds. Bitzer, Black and Wallace (1971).

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reality, a new message set, which appeared to make them more critical and more conscious users of

the platform as a result. These users were not power users, but ordinary people (Madrigal 2015).

Again, like Brummett, I consider the primary audience for rhetorical theory and criticism to be

exactly that: ordinary people, non-scholars (Brummett 1984, p. 102).

The potency of the field of rhetoric is, in my opinion, that our findings can enrich “the stock of

general knowledge possessed by ordinary people” (Brummett 1984, p. 103) – we can affect the

ways people assemble message sets, and make them if not more capable, then at least more critical

and conscious of their rhetorical world and the way it is constructed by themselves or others. Our

increasing presence or even existence online seems to make it all the more important that rhetorical

scholars, what Brummett calls the “gatekeepers” of rhetorical theory and criticism, concern

themselves with the power structures underlying digital rhetorical life. As a facilitative thinker,

Brummett allows the rhetorician an ideological and at the same time practical aim: To enrich

people’s experiences of rhetorical transactions in the world – and perhaps to notice them in new

areas altogether. Following the aforementioned Aaron Hess, who also adheres to Brummett’s

sentiments regarding the role of rhetoric, it is important that we publicly discuss the impact of

technology such as algorithms in order to alleviate an ongoing problem of political polarization

(Hess 2014, p. 18). This notion will be pursued in Part I and III. All in all this is, humbly, the

conversation I hope to participate in with the work carried out in this thesis: To contribute to an

increasingly conscious and critical consumption of algorithmic Internet products such as the FB

News Feed, especially given how seamlessly such products are made to integrate with our day to

day lives, psyche, and sociality.

2.3 Methodological considerations

2.3.1 The algorithm, the case, and the missing link There is a big ‘however’ to be addressed in the context of this thesis, and what I set out to do in it.

Even though I will, as outlined, argue in Part I that rhetoricians should consider algorithms to have

rhetorical properties, there are some obvious difficulties in arguing that we should study or analyse

the algorithms as they are. Given that algorithms are computer code, structures of information

meant for robotic interpretation, very few rhetoricians will be equipped to comprehend and translate

their meaning into something worthwhile rhetorically (or, at all). This is not mentioning the fact that

algorithms in many cases, and particularly those of Google, FB, and other data behemoths, are well

kept business secrets. As researchers of the effects of algorithm awareness Kevin Hamilton,

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Christian Sandvig, Karrie Karahalios and Motahhare Eslami put it: “So many algorithms are buried

not only outside of human perception, but behind walls of intellectual property” (2014, p. 632).

While that might be a topic worth discussing on a societal level – why we are not allowed in on the

structures that influence our online existence, and how we ‘feed the machine’ – it is not the

undertaking of this thesis. Even if we could access this information, there would, again, still be a

long way to go in terms of us being able to decipher it meaningfully. This, however, does not mean

that we are not able to treat the concept of algorithms as frontrunners like rhetorician Aaron Hess

show us through his work (2008; 2009; 2014). Like Hess, I believe we should stretch our rhetorical

capabilities as far as the flexibility of our discipline allow. Given that I cannot access or assess an

actual algorithm, I emulate Hess’ work, and do what I can: in the first part of the thesis, I treat the

concept of algorithms and discuss and define them as having innate rhetorical qualities. In Part II,

the analysis part of the thesis, I introduce relevant theory and analytical tools prior to analysing

rhetorical artefacts from the FB case of 2014. Thus, Part II is closer to a traditional, textual,

rhetorical analysis. The chosen case allows me to analyse an occurrence that is symptomatic of

what I consider to be a more general issue of concern, namely that algorithms, one of the most

powerful influencers of our digital communicative co-existence, are either unknown or

incomprehensible to a majority of the people that are influenced by them. The case I employ in this

thesis make several points evident in this regard, particularly through the reactions of FB users

becoming aware of the role algorithms play online. The third and final part tie Part I and II together

in a discussion of the wider societal and rhetorical implications of algorithms, as levels of

awareness vary between those managing the algorithm, the providers of algorithmic media, and

their subjects, the users.

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3.0 Part I: Theory This part of the thesis introduces algorithms and defines them rhetorically. The starting point for

this conversation is a distinction between personalization and customization as tendencies in online

environments today.

3.1 Personalization versus customization These two words are at times thrown around simultaneously and employed to signify the same

tendency in our online lives as becoming increasingly focused on individualization, tailored

marketing and targeted ads. However the concepts of ‘personalization’ and ‘customization’ contain

very different rhetorical implications for the users experiencing them, particularly relating to the

rhetorical concept of agency9. In the pursuit of a rhetorical definition of algorithms as persuasive

constructs imbued with significant power, ‘personalization’ in particular becomes interesting. The

following sections outline the differences between customization and personalization, and

introduces personalization as the sphere of meaning wherein algorithms belong, following Sundar

and Marathe’s findings in “Personalization versus Customization: The Importance of Agency,

Privacy, and Power Usage” (2010).

3.1.1 Customization: Choosing individualization While both customization and personalization relate to the tailoring of content for online users, the

process through which this tailoring comes about varies greatly between the two. Customization is

“a highly user-driven process of tailoring” (Sundar & Marathe 2010, p. 301), as it entails choices

that a user must actively make on an interface – such as choosing the colour of a homepage, the font

of text or the statement you want the words to form, or the options the user wants to be shown in a

drop-down menu. Customization lends an explanation to the psychological appeal of tailored

content online by referring to a greater sense of agency, as users become gatekeepers of their own

“information universe” (Sundar & Marathe 2010, p. 298-299). This type of individualization of

content is labelled user-initiated customization (UIC), or adaptable hypermedia (Sundar & Marathe

9 For the purpose of this thesis, I subscribe to what we might label a Western agency definition, which the likes of Campbell (2005), Taylor (1985), and Turnball (2004) are proponents of. This definition of agency focuses on the individual, and can be summed up as the innate human capacity to inquire and act upon evaluations (Campbell 2005, p. 3; Turnball 2004, p. 208).

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2010, p. 300-301). The important take-away is that the agency to decide on the main activities and

choices concerning the users’ information universe is located with them.

3.1.2 Personalization: Assuming individualization Personalization lends an explanation to the psychological appeal of tailored content by referring to

“positive content attributes” as users perceive what they are presented with as relevant to them and

therefore good (Sundar & Marathe 2010, p. 299). Personalization is also labelled system-initiated

personalization (SIP), or adaptive hypermedia, as the tailoring process is located not with the user

but with the system, underlining the system’s capacity for adaption towards the user (Sundar &

Marathe 2010, p. 300-301). An important feature of this design is that, in order to “offer these

tailored services to consumers, automatic personalization systems gather user browsing behaviour

data in two ways – overt and covert” (Ibid.). The overt method is well known even among non-

power users – websites will openly ask for a user to register their name, birthday, gender,

relationship status, and so on. The covert method, on the other hand, is, as the name would imply,

more opaque to non-savvy Web users. This includes the placement of cookies in browsers that then

monitor user behaviour on a given site (Ibid.). In other words, the active agent is the system, the

passive the user.

3.1.3 Personalization and the problem with privacy There are obvious differences between customization and personalization, and the underlying

assumptions for each of them affect the system-user interaction that follows. The problem with

personalization, the sphere of cookies and algorithms, is that the covertness of the system means

that many users are unaware of the tasks being carried out on their behalf. Even more problematic is

it that there appears to be a general lack of knowledge and awareness of the presence and workings

of algorithms and cookies. This is where Sundar and Marathe stand out in their field, for as they

point out themselves, “much of the personalization literature focuses on the end result (tailored

content) rather than on the process of tailoring (who does it)” (2010, p. 301). In other words, the

focus of literature on the matter deals primarily with how to make the user experience as gratifying

as possible by tailoring content as specifically to the user as possible. The design of the

“information universes” lies with systems that rely on vast amounts of data and personal

information in order to gratify and reach the end goal of tailored content. This focus on the end-

product misses out on the question of who the tailors of the content are, which in less opaque media

types such as news papers would be considered a perfectly normal, critical inquiry to make; we

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consider who writes the news paper articles we read, since we seem to recognize that it influences

the finished content. In their study, Sundar and Marathe (2010) pursue the same critical questioning

by making users aware of the algorithms and cookies that collect and sort information for them as

they use certain sites. This results in Sundar and Marathe arriving at an important conclusion

relating to this question. Their findings show that our sense of privacy and perceived privacy are

much more important to us than it is to receive tailored content (2010, p. 317). While achieving the

most precisely tailored content was indeed experienced as gratifying based on perceived

convenience for some of the non-power users that participated in the study (2010, p. 314),

participants became suspicious and adjusted their behaviour when made aware of the sorting

mechanisms of algorithms (2010, p. 317). Sundar and Marathe’s findings show how users, when

already aware or made aware of it, “did not feel secure with [a] Website automatically collecting

information about their browsing behavior [sic]” (Ibid.). This was specifically linked to the use of

SIP, and the researchers use their concluding remarks to underline the importance and prevalence of

the privacy concern of Web users:

In conclusion, privacy turns out to be a key predictor of user attitudes toward personalization and customization... Low privacy, (...) appears to be a key psychological concern for users, forcing power users to take personal control of the system by engaging in effortful customization and discouraging nonpower [sic] users from effectively using the system.10

The concluding observations from Sundar and Marathe provide a fitting link to a further look at

algorithms and their capabilities as rhetorical constructs, and to the later analysis. The privacy

concern of Web users that is outlined above appears to be a consequence of knowledge and

awareness of the presence of the systems that facilitate the perceived privacy threats. In other

words, the users that were made aware of the existence of the measures put in place to provide

personalized content were concerned by them, and were more hesitant to use the services of

websites that entailed their use as a result. It seems to imply, following Brummett’s (1984) earlier

points, that certain uncritical and perhaps even unaware message sets about what it implies to exist

online today are in place, resulting in a particular world view. Again using Brummett’s terms,

‘ordinary people’ appear to be unaware of the underlying, powerful structures of devices they

employ as a stable part of their daily lives. As one of the authors of the FB study, Jeff Hancock,

later put it:

10 Sundar & Marathe 2010, p. 318-319

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“I’m not sure whether this means we need to bring in an education component to help people understand that their news feeds are altered all the time by FB? But the huge number of e-mails about people’s frustration that researchers would change the news feed indicates that there’s just no sense that the news feed was anything other than an objective window into their social world.”11

As the analysis will develop on, the tech-community was in no way surprised by the news of the

study, or by the workings of the News Feed algorithm – they were well aware of it. As mentioned

before, I expected the debate to concern algorithms and the power they and the digital institutions

based on them hold in today’s society. As the findings of the analysis will show, the reality of the

debate was quite a bit different, and, in the pursuit of an educational end, there appears to be a need

to bring the workings of algorithms out into the open more than they already are. By this I do not

refer to the technical measures of algorithms, which for the vast majority of people would make

little to no sense, even if we imagine companies like FB would release such profitable secrets for us

to examine. I refer to their capabilities towards altering communicative realities, prioritizing some

information over other, and shaping user interactions – in other words, their rhetorical potential as

tailors of our online experiences.

3.2 Algorithms: Towards a rhetorical definition Algorithms are a potent part of our still more personalized online experiences. As mentioned in the

introduction of this thesis, scholars are increasingly mapping out software, information and new

media as integrated and even constitutional to our way of being. In David Beer’s words, from

“Power through the algorithm? Participatory web cultures and the technological unconscious”

(2009), “information [is] becoming a part of how we live, (...) the things we encounter, our way of

life. The result is that information is not only about how we understand the world, it is also active in

constructing it.” (p. 987-988). This indirectly highlights the significance of the way in which this

information is presented to us, or made to ‘construct’ our world, since the way in which we create

meaning based on the communicative world we exist in influences our actions – and inactions. As

Beer states, “the emergent technologies do not just gather information and hold it, they also use it in

a variety of ways” (2009, p. 988-989). One of these ways is making the information ready for

algorithmic consumption, in order to then turn the flow of information back towards the user,

providing content (such as ads, campaigns, even the suggestion of ‘new friends’) based on this

information. This process creates the most significant stream of income for a company like FB, and

has given the News Feed a position as “one of the most influential products on the Internet”

11 Jeff Hancock in Jay Rosen’s blogpost “Why Do They Give Us Tenure?” (2014)

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(Luckerson 2015). Beyond that, the tasks algorithms perform have qualities we might not

immediately associate with digital command structures – they facilitate a new form of Burkean

identification, affect agency, and perform persuasive acts, thus giving rise to if not a redefinition

then at least a rethinking of some of our core concepts in the field of rhetoric.

3.2.1 Algorithms, Burkean identification and digital rhetorical identification Earlier on algorithms were defined broadly as command structures that give instructions to

machines – be it robots or other forms of computers12. Moving on to a rhetorical definition of them,

I turn to aforementioned Aaron Hess’ “You Are What You Compute (And What Is Computed For

You): Considerations of Digital Rhetorical Identification” (2014). In the following, Hess’

observations as they pertain to identity, Burkean identification, and the role algorithms play therein

are employed as a starting point to build upon with additional theories. The aim of the following

sections, thus, is to explain and display the rhetorical qualities of algorithms such as the one

governing the FB News Feed13.

Similar to Wegner and Ward’s (2013) findings mentioned in the introductory part of this thesis,

Hess contends that “computers need to be theorized as integral parts of communication and

rhetoric”, and not just “as a neutral device through which we speak” (2014, p. 2). Hess is interested

in the way in which digital communication technology is augmenting processes of identification,

thus influencing our offline and online sense of identity (Ibid.). This is important, since our sense of

identity have “profound consequences on public deliberation and interaction” (Ibid.). Hess refers to

Walter J. Ong’s concept of interiorization14 to explain how a previously external phenomenon can

become second nature to the majority of a culture in question - like technology has become to most

of the Western civilization (2014, p. 5). In relatively homogenic societies where access to these

types of technologies is widespread, the concern for the impact on the citizen body seems

warranted: "Interiorization of a new technology influences the way thoughts are structured,"

(Calleja & Schwager 2004, p. 8). Since some of the largest platforms we access through our

technological devices are social networking sites, the question of how we are encouraged to identify

with others on these sites becomes pertinent. The following traces the concept of identification from

12 See ‘1.3 Adressing the elephant: Algorithms’. 13 A gigantic (and for good reasons unknown) amount of command structures inform the News Feed, and this formulation is not meant to undermine that reality. For a qualified estimate of the technicalities behind the News Feed, see Kincaid (2010). 14 Walter Ong, Orality and Literacy (New York: Routledge, 2004).

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its origins with infamous rhetorician Kenneth Burke (1969a) to the redefinition provided by Aaron

Hess in 2014.

Burkean identification In pure identification there would be no strife (...) But put identification and division ambiguously together, so that you cannot know for certain just where one ends and the other begins, and you have the characteristic invitation to rhetoric.15

Such goes a passage from the hallmark piece of rhetorical literature that is Kenneth Burke’s A

Rhetoric of Motives in its revised form from 1969. It provides an apt introduction to the relevance

of Burkean rhetoric towards the News Feed algorithm, as it lines up the “invitation to rhetoric” that

lies within the processes of identification and division. As the famous quote and definition of

Burkean identification goes: “A is not identical with his colleague, B. But insofar as their interests

are joined, A is identified with B. Or he may identify himself with B even when their interests are

not joined, if he assumes that they are, or is persuaded to believe so” (Burke 1969b, p. 20, my

emphasis added). Identification in itself, thus, is not our default setting. As Burke underlines,

identification works from the presumption that we are in fact divided, and identification as such “is

compensatory to division” (Burke 1969b, p. 22). Remembering FB’s own description of the

function and purpose of the News Feed, as it “helps you to see the most interesting stories from the

friends you interact with the most” (FB n.d.), creation of identification in the Burkean sense would

seem to be one of the main purposes of the algorithm. It is programmed to show us posts and people

it expects us to like, and to identify with, so that we may feel as ‘connected’ as FB so famously

strives for16. Another important Burkean concept related to identification, namely that of

consubstantiality, becomes pertinent as an extension of this. Consubstantiality is, to borrow Hess’

description, “the act of two substances meeting through communicating” (Hess 2014, p. 7). This

leads us on to Aaron Hess’ (2014) development of Burke’s identification, which he labels digital

rhetorical identification. Firstly, a closer look at Hess’ view of the role of digital technologies in the

field of rhetoric.

15 Burke 1969b, p. 25 16 “We connect the world” is a hallmark FB quote. See Mark Zuckerberg’s personal post from August 21, 2013 for an example: “For nine years, we’ve been on a mission to connect the world” https://www.FB.com/zuck/posts/10100933624710391

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Hess: Digital technologies promote identification

To Aaron Hess, the relevance of Burke’s concept of identification and consubstantiality towards

modern rhetorical life online is indisputable. Hess sees one of the main accomplishments of the

digital media through which we now interact and communicate, to be that of facilitating

“contemporary identification” (Hess 2014, p. 6). The Burkean definition of identification as an

exchange between identities, as hinted at in the quoted passages from Burke himself in the previous

section, is carried on in Hess’ interpretation of its contemporary relevance, as he reiterates that

“identification focuses on the process of identities meeting through communication” (Ibid.). Hess

adds, importantly, that today “digital technology [is] inherent to that process” (Ibid.).

Hess subscribes to Marie Hochmuth’s17 contention that while persuasion and deliberative design

was at the centre of the ‘old’ rhetoric, identification and the more ‘unconscious’ appeals that go

along with it as we seek to connect with each other are the core concepts of the ‘new’ rhetoric (Hess

2014, p. 7). By ‘new’, Hess means present-day, and from what the article further deals with, the

future appears to be included as a part of this tendency as well. In this line of thought, “the purpose

of rhetoric is more foundational to the psychological nature of humans,” given our almost constant

efforts towards connecting with others (Ibid.). If the main purpose of rhetoric is to function towards

our identification and consubstantiality with others, then the devices that we put in place to perform

some of these functions for us require our attention. Today, these devices are to be found in the

aforementioned digital technologies that Hess himself notes to be “inherent” to the process of

contemporary identification (Hess 2014, p. 6).

Why is it important to concern oneself with such a process as the one Hess presents in his idea of

contemporary identification? And in particular, what significance does it carry towards algorithms

as rhetorical constructs? Hess answers these questions himself. It bears significance to deal with the

way identification and consubstantiality is facilitated in our societies and communicative

environments, because “the psychological self is always seeking unity with others” (Hess 2014, p.

7). While that statement in itself might appear flimsy or idealistic, on a societal level it is anything

but. Processes of identification govern the way in which we position ourselves politically, socially

and professionally – in other words the way in which we construct our identities. As Professor of

Rhetoric Diane Davis puts it in “Identification: Burke and Freud on Who You Are”, identity is “the

enactment of a series of dissociated and frequently contradictory roles defined by the groups with

17 Marie Hochmuth (1952), “Kenneth Burke and the ‘New Rhetoric’”, Quarterly Journal of Speech, Vol. 38, p. 136.

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which one identifies” (2008, p. 127). If these groups are presented to or constructed for us by means

beyond our comprehension or power, these means must be scrutinized. While Hess contended,

alongside Hochmuth, that persuasion was the core concept of the old rhetoric, identification in itself

has persuasive properties if employed as a means towards that end. As Burke states,

“consubstantiality, either explicit or implicit, may be necessary to any way of life (...) life is an

acting-together; and in acting together, men have common sensations, concepts, images, ideas,

attitudes that make them consubstantial” (Burke 1969b, p. 21). As we “seek unity with others”, we

develop a “new sense of motivation for the individual actor” (Hess 2014, p. 7). This makes evident

the importance of how and towards what end we are made to experience and enact consubstantiality

online, in places such as FB.

Digital rhetorical identification

Our interactions with others matter, as they shape our perceptions of self in a personal, but also in a

societal and political context. Today, much of our interaction takes place on online platforms such

as FB. Interaction such as chatting, posting and writing to each other can be downplayed as

‘innocent’ and comparable to sending small ‘letters’ to each other. While that could be partially true

for the small-scale actions that take place on FB, the question of the communicative environment as

a whole is in an entirely different league. “Identity [is] made through language with others”, but as

Hess goes on to state, “identification has been altered by the pervasive use of digital technology”

(2014, p. 7).

To encompass the hidden impact digital technology has not only on us, but also on rhetoric, Hess

employs a redefinition of Burke’s identification. He labels the adopted and adapted concept digital

rhetorical identification, and explains it as “a process of technological unconscious

consubstantiality, through which users are provided and believe in information and argument based

upon their digital substance” (Hess 2014, p. 9-10). The idea is that our technology now performs

some of the social, psychological and rhetorical tasks that we otherwise would carry out amongst

ourselves. The identities we are partially granted, partially constructing online are moulded by

Internet cookies and algorithms, as the first delivers data bits about our behaviour, and the second

digests what the cookie feeds it: “Our identities – or substances, to use Burke’s language – are

comprised of our neuropsychological and computer programming, developed through our

interactions with people and computers alike. Cookies, and their respective algorithmic

implications, forge our neurotechnological identities” (Hess 2014, p. 8).

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As we carry out tasks and enjoy recreational time online, “digital dossiers”, a term employed by

Daniel Hillyard and Mark Gauen (2007) as they discuss issues of protecting personal information,

are being compiled about us. This happens continuously across platforms. Obvious (and lucrative)

uses for such dossiers are the ever-present targeted ads and other marketing attempts towards

profiting off of individualization, as previously discussed. However, the impact goes beyond mere

profitability, despite it being no doubt a key incentive for the measures to exist in the first place. As

hinted in the above quote by Hess, the digital dossiers, and for that matter the computers through

which they are collated, become “an extension of who we are” (2014, p. 10). Our choices, actions,

comments, searches, purchases, readings and viewings online shape us, also offline, and influence

the digital environments that we in turn are presented with when we log back on. This results in an

important observation regarding algorithms and the rhetorical process of identification as discussed

so far. Hess phrases it this way: “Identification with others appears at the algorithmic level (...) In

short, users create digital substances that are concurrent with and affect psychological substances”

(Ibid.). In other words, our online self is not distinct from our offline self, but rather an extension of

it. Based on this extension, as it is interpreted by for example the News Feed algorithm on FB, we

are presented with a select set of news, ads, and people.

From identification back to division

The important takeaway from the above presentation of both Burkean identification and Hess’

novel interpretation of it is the significance the concepts bear towards the ongoing shaping of our

communicative environments online. If the underlying assumption operated into an algorithm is that

I prefer to see, read about and hear from people who are akin to myself, and that I prefer to have my

once stated preferences reintroduced to me over and over to have my tastes reaffirmed as desirable,

then I am indeed not looking through an objective window into my social world, as Jeff Hancock

put it. In fact, the effect would appear to be more comparable to that of a mirror. The hierarchies of

information created by technology on our behalf have potentially far-reaching consequences for

public debate, social life and our positioning on policies, if we are in fact oblivious to our

systematic exposure to a targeted set of messages. An important possible ramification of this

process is what is known as the echo-chamber effect, something the following section will address

as the implication of algorithms towards rhetorical agency is treated.

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3.2.2 Algorithms and agency It is not necessarily obvious to the average Internet-user going about their daily digital business that

their options are in fact limited by the workings of algorithms. As discussed previously, algorithms

perform processes of identification on our behalf, and assume our future preferences based on our

past online behaviours. When the underlying assumption is something along the lines of ‘likeness is

good’, then we end up with a drawback that Hess describes as such: “the online circulation of

knowledge serves as an echo chamber of personal desire and opinion rather than giving users

diverse perspectives. This effect bleeds into offline rhetorical practices, limiting the circulation of

public knowledge and argument” (2014, p. 1). This introduces the discrepancy between the Internet

as on one side an apparently wide-open space filled with information and possibilities, and on the

other side the opaqueness of the online environment meeting most people as they utilize the

common and popular websites. It also puts forward the notion of an echo chamber being created

partially by us, partially for us. Rhetorically, this is a significant hypothesis, since its realization

would impact public deliberation and the formation of public opinion18, and the circulation of

knowledge and argument mentioned by Hess.

Creating an echo chamber Algorithms, and cookies for that matter, end up collecting and sorting information on our behalf,

based on the digital personalities we convey through our online behaviour. While a lot of services

that make life easier for us arise from this, so do problems. One important notion presented by

Hess, particularly in his earlier work (Hess 2008), is the idea that algorithms by their function as

facilitators of identification create “tracts on which [users] will continue to progress through the

Web [which] keeps the user confined within a set of experiences and interactions” (Hess 2014, p.

10). This is what Hess labels an echo chamber effect. An issue closely related to it is the fact that

“the structural components of web searching and cookies are defined by privately owned interests,

but are used every day by millions of public users for information seeking” (Ibid.). Since the

majority of users visit a select number of major sites repeatedly, and since we attribute an

increasing number of services to these sites19, the use of the same very sites is reinforced. In Hess’

18 Public opinion as a concept will be employed sporadically through this thesis. It is however not a fix-point in itself, and will not be defined further in-text. I concur with Gerard Hauser’s orientation towards public opinion as a process: It represents the opinion of the many, and is expressed and experienced in a “broad range of symbolic exchanges whereby social actors seek to induce cooperation” (1999, p. 90-91). 19 Such as FB providing news, see ‘1.2 What News Feed feeds us’.

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words such sites “add to our existing equipment for living” by offering strong suggestions, which

will affect future decisions (2014, p. 12). This, in turn, influences publics and the production of

deliberative rhetoric on a vernacular level: “Political information is bound up in our own digital

identification process, meaning that we are reinforced and rewarded for believing in the things that

we (likely) already believe in” (Hess 2014, p. 13). This is an important aspect of the agency-

limiting qualities of algorithms, and according to Hess these processes are “even stronger” on

“social networking sites, such as FB”. As Hess proceeds, “if a user believes in one side of a political

argument, it is likely that digital cookies and their algorithms will continue to find information that

is relevant to and supportive of that position” (Ibid.). Thus, an echo chamber is created, and,

because of the subtlety with which it is, we can move deeper and deeper into it without being aware

of it even existing.

Agency in an echo chamber

To address agency further, some of the observations from the discussion of identification and

consubstantiality must carry over. The concepts become intertwined, as they co-exist as parts of the

function that end up limiting our rhetorical ability and possibility to act. It is our past behaviours –

searches, ‘likes’, people we associate ourselves with, write to the most or ‘follow’ across platforms

– that make up our “core digital substance”, which in turn gets served back to us as we utilize

online platforms now (Hess 2014, p. 13). Consubstantiality ends up as a service provided

seamlessly to us, as “algorithms (...) predetermine the type of website that would be most fitting for

each individual” (Ibid.). This makes up what Hess calls ‘digital consubstantiality’: “The user is

simultaneously active and passive in the identification process; active in searching for ideas and

knowledge, but passive in the function of the algorithm that groups people together” (Ibid.). Thus,

cookies and algorithms function as vehicles of identification and consubstantiality in a Burkean

sense, but do so implicitly, in the backdrop of our consciousness. In Hess’ words, “it is assumed by

the machine on behalf of the user” (Ibid.). The creation of echo chambers is a likely result hereof,

since increasingly, “your computer is a kind of one-way mirror, reflecting your own interests, while

algorithmic observers watch what you click”, in the words of author and Internet activist Eli Pariser

(2011, p. 3). By associating ourselves, perhaps unconsciously, with something or someone over

another, we are participating in a potentially agency-limiting practice that influences us in return.

The echo chamber effect would, if taken further, augment the polarization of groups of individuals

within micro-environments such as FB, but potentially also facilitate that same effect in a macro-

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setting, such as society at large. If we are primarily shown ideas and knowledge that we already

agree with or have sympathy towards, while believing to experience an objective view of the world,

we might be unconsciously participating in a democratically undermining and agency-depriving

discursive practice. It can hardly be thought to be sustainable for an educated and informed societal

conversation that each of us increasingly are made to believe, unconsciously, that we are in fact

right and stand mostly unchallenged in our views, whatever they may be. This is of course an

exaggeration of the tendency, but an important one to make in order to consider the potential

impacts of our digital communication technologies, as they create “a sense of identification and

“we-ness””, and a “corresponding ‘they’” (George Cheney in Hess 2014, p. 13). In other words, it is

an important exaggeration to make to accentuate even the possibility that we are creating and in

turn depicting an increasingly polarized society. We are of course not completely underlying a

“self-serving environment without argumentation or contestation” as it is, but we are somehow

partially in the dark when it comes to how objective our window into the world through digital

technology really is (Hess 2014, p. 15). Our ability to act on an informed basis is limited, when the

average user has little to no knowledge of the processes carried out in the backdrop of their digital

presence. Our rhetorical agency is limited, since our actions within this system are predetermined to

move in some direction or another, based on our past preferences. The functions in place occur “in

ways known and unknown to the user, appearing actively in search terms and passively in the code”

(Hess 2014, p. 14). As will be discussed in more detail in Part III of this thesis, and here Hess again

provides an apt formulation, “the consequence (...) looms large over the field of rhetoric and

argumentation, especially in the public sphere” (Ibid.). The following section develops on that

notion.

3.2.3 Algorithms as persuasive structures This third and final point relating to the rhetorical nature of algorithms extends on the

persuasiveness of algorithms, as it relates to the underlying assumptions present in products such as

the News Feed algorithm. Hess’ concept of ‘trained incapacities’, again a remodelled Burkean

term20, is introduced as a persuasive measure, and incorporated into a discussion of aforementioned

David Beer’s observations in “Power through the algorithm? Participatory web cultures and the

technological unconscious” (2009). The aim of this section is to show how algorithms in subtle

20 Kenneth Burke, Permanence and Change: An Anatomy of Purpose, (Berkeley, CA: University of California Press, 1954), p. 48.

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ways are highly influential measures in modern day processes of argumentation and public

deliberation. Algorithms are defined as persuasive given their power to direct both the attention and

the information searches of its subjects – us – and the aforementioned underlying assumption of

algorithms that we want more of what we already want – a “setting” which we are not able to

change or influence.

Subtle persuasion, significant power

Algorithms are persuasive because they train us to behave in certain ways, but the trick is that they

do so without marking their presence, or revealing their actual function. The word ‘train’ is

deliberately chosen here, as it relates to a core concept in a rhetorical understanding of algorithms,

namely that of ‘trained incapacity’, as introduced firstly by Kenneth Burke21, secondly by Hess

(2014). Since Hess’ redefinition is specifically pertinent to algorithmic media, it is the one chosen

for further discussion here. However, I do want to note my pleasant surprise in how significant and

productive the thinking of a rhetorician such as Burke, a dramatist, should prove to the rhetorical

explanation of complex technological advances in our global society today. In a way it underlines

the value and meaning of fundamental thinking and the concepts it produces; in a field such as

rhetoric, it obtains timelessness through continued relevance and applicability.

A trained incapacity in Hessian understanding covers the effect of our still intensifying use of the

Internet, and the cookies and eventually algorithms that govern and go with it. The effect becomes

one of ‘training’, because reoccurrence and repetition characterize the way in which we are made to

interact with knowledge and information online. In Hess’ words, “the more users engage in search

engines (...) the more [cookies and algorithms] include information that is considered relevant and

exclude information deemed unimportant to the user” (2014, p. 15). To somewhat oversimplify it:

The more we move around, the smaller the space gets. The effect, then, becomes one of

‘incapacity’, since the result of the repeated exposure to similar information is that “the user is

trained in their views and less likely to recognize other perspectives” (Ibid.). This is subtle

persuasion at work, which ends up informing “argumentation practices and public deliberation in

profound ways” (Ibid.).

21 Kenneth Burke, Permanence and Change: An Anatomy of Purpose, p. 48.

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Polarizing publics

If we are trained, repeatedly, to be less sensitive to other views than our own, and encouraged to

indulge in our currently held persuasions, we are slowly and perhaps unknowingly being led down a

narrowing cave of self-righteousness. If the aim is for everyone to at all times feel as unchallenged

as possible online, whatever his or her conviction may be, we end up being done a great disservice

as a society. This is of course taking simplifications to an extreme, but again an arguably

worthwhile one at that. The presence, and our simultaneous awareness, of diversity of opinion,

political stratification within groupings, and the value of counter-arguments in testing concepts and

beliefs, appear undermined in the name of agreeableness and comfort: “As unconscious devices,

algorithmic digital cookies positions users in polarizing groupings of knowledge (...) these

groupings foster inbreeding of argumentation without the users’ knowledge” (Hess 2014, p. 16). It

is important to underline that what is posited here is not “that specific arguments are guided by

cookies”, or algorithms for that matter, but rather, again following Hess, “that the topics and general

lines of argument to which we are exposed are driven by our search histories” (Ibid.). For many

users, this process will not be an obvious one to spot and be conscious of, since “today’s algorithms

provide users the veneer of diverse knowledge sources and neutrality, while merely replicating what

is already desired for users” (Ibid.). Polarization, as Hess goes on to argue, is the outcome, as the

reaffirmation of “preexisting [sic] views held by individual users [lead] to increased political

polarization as a consequence of digital technology by its limiting of diverse interactions” (Ibid.).

Hess then carries his argument towards Michael Warner’s “Publics and Counterpublics” (2002),

and the view of a public as a set of stranger relations, which Hess believes the process of

polarization breaks down. Hess contends that ultimately this result in a generally diminished ability

to empathize within publics and across political persuasions, and that this tendency extends to the

offline world. As we become less sensitive to “a variety of practices of invention (...),

argumentation practices are drastically affected in traditionally understood offline spaces as well”

(Hess 2014, p. 17). These are the ways in which Hess sees digital technology as interfering with

“how we engage in and evaluate public argument” (Ibid.). All in all, this thesis answers the call of

Hess for further inquiry into “the impact of digital code and software (...) on public deliberation and

debate” (2014, p. 18).

3.3 Beyond Hess: Algorithms at work Hess’ investigations into the combination of rhetoric and digital code provide us with a definition of

algorithms as essentially rhetorical constructs that have the ability to shape the formation of publics

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through digital rhetorical identification, with potentially far-reaching effects. In this section, I look

beyond the work of Hess to argue the existence of what I label a ‘knowledge gap’ between

providers and users of algorithmic media. The concept addresses the distance of comprehension that

the FB case made evident, which Part II will elaborate on: A majority of FB users had little to no

understanding of the media they were frequenting, whereas the providers (FB) and outsiders (Tech-

community) had all the understanding. Their disbelief was directed at the surprise of the users.

While the analysis reveals the existence of a knowledge gap, the following defines the particulars of

the concept.

3.3.1 Locating a knowledge gap

Even before the publication of the FB study, which marked a point of realization as to how little

many people knew about a media they frequented daily, journalist and Editor-in-Chief Alexis

Madrigal posted an article on the site Fusion under the headline “Many, many FB users still don’t

know that their feeds are filtered by an algorithm” (Madrigal 2015). In it Madrigal articulated the

idea of a knowledge gap: “For heavy FB users, let alone social media gurus, the idea that FB’s news

feed is filtered by an algorithm is very, very old news. But a majority of everyday FB users in a

recent study had no idea that FB constructs their experience” (Ibid.). The study Madrigal refers to is

the aforementioned research done by Eslami et al. in a paper carrying the title ““I always assumed

that I wasn’t really that close to [her]”: Reasoning about invisible algorithms in the news feed”

(2015). In it participants were exposed to the presence of the FB News Feed algorithm and made to

understand the work it carries out on their behalf. In this way, the study addressed the possibility

that users were not aware of the workings of the site - an assumption that turned out to be correct.

Upwards of 60% of the participants in the study had no idea that the News Feed algorithm would

hide some stories and show others (Eslami et al. 2015). The users interviewed simply believed that

everything they saw in their News Feeds was an “objective window into their social world”, as

researcher Jeff Hancock would later put it (Hancock 2014). In order to counter the imperceptibility

of the News Feed algorithm, Eslami et al. developed an application called FeedVis that showed

participants the stories that were filtered out of their original News Feeds (Eslami et al. 2015). The

pattern of reactions in participants moving from ‘not knowing’ to ‘knowing’ is worth noting: “We

discovered that strong initial negative reactions to the mere presence of an algorithmic filter often

subsided once users understood who and what was being hidden. We followed up with participants

two to six months later and found that their usage patterns had often changed due to the insight they

gained about the algorithm via our study.” (Eslami et al. 2015). In Eslami et al.’s (2015) words,

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participants previously unaware of the role algorithms play in curating the contents of their News

Feeds initially react with “surprise and anger”. Interestingly enough, following up on the study

months later the researchers found that “for most, satisfaction levels remained similar before and

after becoming aware of the algorithm’s presence, however, algorithmic awareness led to more

active engagement with FB and bolstered overall feelings of control on the site.” (Ibid.). The users

already familiar with the existence of the News Feed algorithm were not surprised or angered by it,

instead they noted how this knowledge changed their way of interacting with FB (Ibid.). Aware

participants “stated that awareness of the algorithm led them to actively manipulate their News

Feed, using theories they developed about how the algorithm might work” (Ibid.).

3.3.2 Knowledge gaps and algorithm awareness A knowledge gap, then, might be defined as the distance of awareness exemplified in the two

groups of participants in the Eslami et al. study. The gap becomes apparent when an unaware group

is confronted with new knowledge that suddenly seems to collectively move the group in a

direction, marked by the similar reactions expressed individually by participants in the Eslami et al.

study. The reactions of surprise and anger might in fact be the best detectors of how vast a

knowledge gap has been - the stronger the reactions the greater the gap. This is of course my

musings about a concept made up for the occasion, but the question of algorithm awareness is a

very real one. In “A Path to Understanding the Effects of Algorithm Awareness”, Hamilton et al. set

out to uncover exactly that: “How does understanding of algorithms affect use?” (2014, p. 632).

The authors note that algorithm awareness, and in this context the existence of a knowledge gap,

does not necessarily relate to the level of education or professional status of the individual users.

Unawareness of algorithms and the role they play in filtering information exist on all demographic

levels, even among Graduate Students in Computer Science (Ibid.). The problem, as Hamilton et al.

define it, echoes the motivation for my focus on algorithms in this thesis in the first place: “For

some, such lack of awareness is indicative of successful design - for shouldn’t good interaction

design be invisible? For others this invisibility indicates that something potentially controversial has

been settled, decided, made static” (Ibid.). The knowledge gap, thus, is an important concept

because it addresses the existence of an unawareness of these potentially controversial measures

being integrated seamlessly into our daily Internet use. The spatiality of the metaphor also implies

the possibility for users to become aware, to cross that gap, and to change behaviour as a result, as

Eslami et al. noted it to be the case (2015).

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3.3.3 The call for transparency: Algorithms and rhetorical citizenship So what are the wider consequences of the matters discussed in the previous? Why do knowledge

gaps matter beyond the fact that some of us stand on one side, and others on the other? In answering

these questions, I concur with Professor Emeritus of Philosophy Lawrence M. Hinman in his

considerations of ethics in search engines and the construction and distribution of knowledge:

“Here, then, is the challenge that faces us: search engines are not just providing access to knowledge, but are increasingly paying [sic] a central role in the constitution of knowledge itself. Such control of knowledge is, in a very fundamental sense, a public trust, yet it remains firmly ensconced in private hands and behind a veil of corporate secrecy (...) Search engines are directly responsible to their paying customers, their advertisers, and not directly to the public users (...) These tangled lines of responsibility, combined with the opacity of the search process, suggest that public mistrust may be the more appropriate attitude (...) Realizing the increasingly important role that search engines play in the construction of knowledge is an important first step toward increasing transparency” (Hinman 2008, p. 75).

I believe Hinman’s observations regarding search engines to be equally relevant in the FB case -

and beyond. If we approach knowledge as a wider concept entailing things such as our sociality,

capacity for co-existence and informed deliberation, then Hinman’s concerns gain a wider

applicability. In other words, we might exchange the word ‘search engines’ with ‘algorithms’. The

call for transparency that Hinman notes at the end of the above quote carries the conversation on

from one that defines algorithms as rhetorical constructs imbued with subliminal messages, to one

that considers the wider potential consequences of our increasing dependency on algorithmic media

types. There might be numerous wider consequences to be named, but the most relevant one to

discuss in the context of the observations made in this thesis is that of rhetorical citizenship. This

point will be defined and developed in Part III, the discussion. Before we get to that, however, the

analysis considers the rhetorical responses to the FB case of 2014.

3.4 Summarization As the previous sections have discussed, we can define algorithms rhetorically as they serve to: 1)

provide digital rhetorical identification between its subjects, 2) affect and to some degree limit

rhetorical agency for its subjects, and 3) function as persuasive constructs that, although subtle, are

a potentially significant behaviour modifier in socio-political settings given their power to inform

argumentation practices and thus affect public deliberation. Having established these

characteristics, algorithms somewhat leave the spotlight of this thesis for the duration of Part II,

where they play a supporting role in the analysis of responses to the FB case of 2014. This is

partially due to, as discussed in ‘The analysis, the case and the missing link’, the fact that I cannot

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assess the actual News Feed algorithm – I rely on rhetorical responses to its presence for critical

assessment. The point of the analysis is to characterize the different reactions from key groups

surrounding the case through pentadic analysis, with a final aim towards showing a real-life

example of knowledge gaps in action.

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4.0 Part II: Analysis This part of the thesis investigates rhetorical responses to an actual incident where algorithmic

power, and the few in control of it in our society, became evident to the public. The analysis seeks

to illustrate how different relevant groupings around the FB case articulated the particulars of the

situation they were in at the time. Ultimately, this is in order for Part III of this thesis to debate the

consequences of knowledge gaps between providers and users of algorithmic media like FB. The

groupings selected consist of:

1. FB

a. Corporate FB, represented by a formal response by Chief Technology Officer Mike

Schroepfer, and

b. Research FB, represented by a FB post by researcher Adam Kramer.

2. FB users, debating in the comment section of Kramer’s FB post.

3. Tech-savvy outsiders, blogging or otherwise writing about the situation.

It was my assumption moving into the analysis of the FB case from 2014 that users, more than

anything, would react to the new available knowledge of the role of algorithms in large-scale media

such as FB. Not that this knowledge in itself by any standards is new – as the analysis will show,

tech-savvy users were utterly unsurprised at the publication of the algorithm alteration study that

the 2014 case in essence was. Previously unaware users, on the other side, displayed the same

strong emotional reactions detected by Eslami et al. (2015) to the news of algorithms being in

control: Anger and surprise. The two main allegations against FB were: 1) that the research was not

up to academic standards, and 2) that the research was unethical. While there might be rewarding

conversations to be had on each of those accusations, the remarkable point about them in the

context of this thesis is what they miss: The type of research FB published in 2014 is being carried

out continuously and routinely, not just at FB, but across the industry of online business. While that

in itself does not form a warrant to conduct substandard experiments or behave unethically, the

bedrock of the issue is that the media is algorithmic – the site, the business, and the online world as

we know it today operates the way it does because of studies like Kramer, Guillory and Hancock’s

(2014). This is not in defence of procedures carried out at FB or anywhere else for that matter.

However the reality remains that algorithms are changeable and manageable, they are human-made

and information is what they run on. What the FB case, through the following analysis, has come to

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illustrate for me beyond anything else is the general lack of understanding of a media type

frequented daily by 968 million people. In other words, the analysis, as mentioned before,

ultimately reveals the existence of people’s reactions to a significant knowledge gap.

4.1 Collecting the artefact The artefacts chosen for analysis in this thesis were collected based on a desire to illustrate not only

how main groupings around the FB case responded to it, but also how the conflict contains and

presents issues that are relevant in society at large. In the following, the guidelines of Elisabeth

Hoff-Clausen as they relate to the creation and stabilisation of online artefacts – a category all of the

artefacts analysed in this thesis belong to – are briefly outlined.

4.1.1 Composing an online artefact In contrast to the analysis of a speech that begins and ends, the treatment of online discourse

involves a process of limitation and composition that precedes the analysis itself. It is the hypertext

status of online discourse that makes the boundaries of individual texts fluid: Hyperlinks, related

articles, commentary tracks following the main text, and so on and so forth – it all challenges the

critic to choose where to end the artefact. As Elisabeth Hoff-Clausen argues in “Online Ethos. Web

rhetoric in political campaigns, blogs and wikis”22 (2008), it is the focus or the particular interest

that the critic approaches her subject with that narrows down the pool of data she will incorporate in

an analysis. Hoff-Clausen introduces the concept of key texts to name the texts or artefacts that will

shed light on and help answer the research question the critic is investigating (2008, p. 65). These

key texts are chosen based on a thorough orientation within several possibly important texts. The

end result of the process, ideally, leaves the critic with a limited number and size of key texts that

are “particularly pregnant fragments” (Ibid.). Thus, the choice of artefacts for analysis is completely

dependent upon the individual critic’s analytical scope and sensibility (Ibid.).

Another important aspect of online artefacts is their continued development and changeability.

Given their belonging to an online and forever editable environment, online discourses are likely to

shift form even as the analytical work is being carried out. Therefore, the process of conducting a

textual analysis of online artefacts also entails stabilizing them (Hoff-Clausen 2008, p. 67). In Hoff-

Clausen’s words, the critic has to co-create the artefact by “selecting, limiting, and at a given time

22 Hoff-Clausen’s (2008) book is in Danish. Any quotes from Hoff-Clausen employed in this thesis are provided in English by my translations.

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stabilizing the web text in a documentable form” (2008, p. 67-68). In this way, the choice of artefact

for analysis is not just a selective process, but also an inventive and interpretive one through the co-

creation of the critic (2008, p. 68). In the context of this thesis, this process is particularly relevant

to the artefact consisting of comments from individual FB users. Following Kramer’s post, a current

total of 160 individual comments make up the ‘conversation’ (Kramer 2014). Out of these

comments the artefact was constructed, based on an initial reading of the entirety of the thread. In

order to stabilise the artefact, the comments were printed out. Only 91 out of the 150 were

eventually employed in the analysis, based on their relevance towards the categories established

after the initial reading. This method is described in more detail prior to the analysis of the

comment thread. In the citation of comments and commentators, typography and spelling have not

been altered except the abbreviation of ‘Facebook’ to ‘FB’. The comments are attached as an

appendix to this thesis although they are freely accessible online, because of potential subsequent

edits and deletions. Each comment is identifiable by the name, date and time23 provided. The other

artefacts will be referenced in-text.

Having explained the process of collecting the artefacts chosen for analysis, the following section

describes the process of analysing them. This includes a brief introduction to pentadic criticism as it

is presented by Sonja K. Foss in her book “Rhetorical Criticism: Exploration and Practice” from

2009, supported by remarks from Kenneth Burke himself.

4.2 Analysing the artefact The theoretical work of Kenneth Burke, which has already been employed throughout the thesis,

allows for the rhetorician to concern herself with motives, the ways that people construct a dramatic

frame around an incident or an action. Who did what, to whom, when and where, with what – and

why? How we fill in the unknowns in that equation affect our view of the world and things that

happen within it. As Sonja K. Foss puts it, “how we describe a situation indicates how we are

perceiving it, the choices we see available to us, and the action we are likely to take in that

situation” (2009, p. 356). Following this line of thought, Burke’s pentad and the pentadic criticism

that goes with it was chosen to assess, in each of the artefacts, the construction of the situation that

the FB case made evident: That algorithms were influencing the online lives of users on sites such

23 All times are in Universal Time, Coordinated (UTC), and listed according to a 24hour time system.

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as FB more than the vast majority of people were aware of. The case also opened up a debate

regarding research practices and ethics.

4.2.1 Performing a pentadic criticism This thesis performs a pentadic criticism and draws the relevant units of analysis in the treatment of

the aforementioned artefacts. A pentadic analysis allows the critic to question the representation of

motives – something that is particularly useful when analysing contesting accounts of the same

incident or event. With the pentad, Kenneth Burke’s five-cornered model of questioning a rhetorical

utterance (or virtually any other type of artefact given the wide applicability of pentadic analysis,

see Foss 2009, p. 357), we can approach the underlying rationales of a rhetor. In Burke’s own

words from his A Grammar of Motives, the pentad, and the dramatism24 it belongs to, helps to

answer the question: “What is involved, when we say what people are doing and why they are

doing it?” (1969a, p. xv). As hinted in the previous section, herein lies the reason for choosing

Burke and the pentad as theoretical and analytical approaches for the purpose of this thesis. For how

do FB and Adam Kramer explain themselves, compared to how the individual FB users portray the

situation? What about the tech community, the outsiders looking in? How is the knowledge gap

addressed? By employing Burke’s pentad, these questions can be answered more precisely, since

“any complete statement about motives will offer some kind of answers to these five questions:

what was done (act), when or where it was done (scene), who did it (agent), how he did it (agency),

and why (purpose)” (Burke 1969a, p. xv). These five questions make out the pentad’s corners.

To use Foss’ description, the two steps in a pentadic analysis are: “1) labelling the five terms of

agent, act, scene, purpose and agency in the artefact; and 2) applying the ratios to identify the

dominant term” (2009, p. 357). In a given artefact, there will be a dominant term out of the five

possible. ‘Dominant’ here means “the most important term among the five and the term through

which everything else happens”, and identifying it “provides insight into what dimension of the

situation the rhetor privileges” (Foss 2009, p. 360). The way to identify the dominant term is by

applying the ratios, the possible combinations of the five terms, to the artefact25. An example could

be a scene-act ratio, where scene is dominant (signified by being placed first) to act – meaning that,

in the artefact, the scene in some way dictated the act (for more see Foss 2009, p. 361). When

24 “The titular word for our own method is “dramatism”, since it invites one to consider the matter of motives in a perspective that (...) treats language and thought primarily as modes of action” (Burke 1969a, xxii). 25 Controversy exists within the literature on the details concerning the possible number of ratios. For more, see Hanne Roer’s “Dramatisk, pentadisk kritik”, in Lund & Roer (eds.), Retorikkens Aktualitet, 3rd edition (2014).

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identified, the dominant term can help the critic to further establish the ideology that protrudes from

the results of the pentadic analysis. The ideologies, or philosophic terminologies, are attached to the

dominant term, and Burke lists them as such: scene – materialism, agent – idealism, agency –

pragmatism, purpose – mysticism, and finally act – realism (Burke 1969a, p. 128). Since the

ideologies in themself are not the focal point of this analysis, they will be introduced as they

become relevant in the findings of each of the artefacts. For the case of consistency, the terms

(scene, agent, agency, purpose, act) will be in italics throughout the analysis.

It is the intention of the analysis to first treat each artefact, identify the dominant term and adherent

ideology, and then compare the results in a discussion of competing ideologies. For each artefact

the headlines ‘(I) The five terms’, ‘(II) Ratios and the dominant term’, and ‘(III) Ideology’

announce the standard elements from the dramatic analysis. Any other additional sections and

headlines relating to the individual content of the artefacts will be added for each of them where

relevant. In this way, this thesis performs a pentadic criticism, and uses it as a stepping-stone for the

discussion in Part III.

4.3 Talking about power: Facebook and Kramer’s post Following the publication of the study conducted by Adam Kramer, Jamie Guillory and Jeffrey

Hancock (2014) reactions poured in from FB users, the academic and professional community –

locally, within the US, as well as globally. As mentioned in the introductory part of this thesis, the

two main points of criticism directed at FB, and the authors in particular, were firstly concerned

with the overall method of the study: to carry out an experiment on a massive scale, to which its

human subjects were unaware and had not explicitly consented to. Secondly, the uproar was a

reaction to the general realization that emotions could be manipulated through altering the News

Feed algorithm – and that someone was in charge. Adam Kramer was the first to post a public

response to the criticism, which he did on his publicly accessible FB page on the 29th of June 2014,

twelve days after the study was published in Proceedings of the National Academy of Sciences

(PNAS). While twelve days might appear a long time at first glance, the response was in fact timely

given that the study did not spark attention before the weekend of June 27-29 2014. FB

headquarters, in the form of Chief Technology Officer Mike Schroepfer, responded on the 2nd of

October 2014, with a blog-post on the official FB site. In the following, a pentadic analysis of first

Kramer’s and then FB’s post is carried out in order to establish first their placement of the five

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pentadic terms, and then the dominant term. As the analysis will show it to become relevant, some

remarks on theory of apologia will be introduced.

4.3.1 Kramer: Downplaying agency and almost apologising Adam Kramer’s post to FB carries a peculiar double meaning in its content and form. It appears on

Kramer’s private FB account as a statement written by him and posted by him for all to see, yet at

the same time, later on in the commentary track to the same post, Kramer writes in his only

response ever in that commentary track: “This post is FB’s statement on the matter.”26. There seems

to be a clash between the medium Kramer chooses for the distribution of the message, and the

communication practice that follows – which is a complete lack of response to any of the 150+

comments posted – something that is noted by other commentators below the post27. Besides this

observation, the post in itself provides an interesting placement of responsibility in the controversy,

which is also presented in a particular way.

(I) The five terms

There are two significant remarks to make on Kramer’s FB-statement. The first one deals with his

downplaying of the term agency, the second with the presence of what I label a semi-apology. The

two remarks will be treated in this order in the following, alongside a labelling of the pentadic

terms, as they are present in his text.

Downplaying agency

Kramer begins his statement by declaring the purpose of the research done by him and his

colleagues to be made up of what appears to be a combination of compassion and business

mindedness: “The reason we did this research is because we care about the emotional impact of FB

and the people that use our product (...) At the same time, we were concerned that exposure to

friends’ negativity might lead people to avoid visiting FB” (Kramer 2014). He quickly moves on to

describe the act following purpose, by writing that what he and his colleagues did was “investigate

the common worry that seeing friends post positive content leads to people feeling negative or left

26 Comment posted to FB by Adam D. I. Kramer, 29th of June 2014, 10:20pm. Access (also to the comment thread) via https://www.facebook.com/akramer/posts/10152987150867796 27 Commentator and Professor of Journalism Jay Rosen articulates this: “Adam has, indeed, opened a dialogue on FB’s research policies, offered a partial explanation (which some have called an apology) provoking reactions and a host of good questions in this thread, and then abandoned that dialogue, leaving many questions hanging” (Comment by Jay Rosen, 1st July 2014).

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out” (Kramer 2014). Scene has the weakest presence of the five terms, being noted as the “one

week, in early 2012” where the experiment took place, the agents of it being “me (...) and Jamie and

Jeff (...) my coauthors and I” (Kramer 2014). While there appears to be a somewhat obvious effort

to establish the alleged “care” and “concern” that motivated the research in the first place, thus

perhaps seeking to render the whole of it more worthy of forgiveness, the interesting part of

Kramer’s post is what I label agency in the context. It is interesting, because it is marked by a

significant downplaying of the ways in which the research came about: “very minimally

deprioritizing [sic] a small percentage of content in News Feed (...) for a group of people (...) for a

short period (...) And at the end of the day, the actual impact on people in the experiment was the

minimal amount to statistically detect it” (Ibid.). Compared to the otherwise relatively neutral,

general and even slightly official-sounding language of the private post, this passage is laden with

“very minimally”, “small”, “short”, and “minimal”. FB users in the comments also note this

apparent effort towards downplaying agency, and one of them, Claire Litton, writes:

“FB is completely opaque, and minimizing the study as being too small to cause an impact minimizes what I see as FB’s real problem: lack of accountability or investment in anyone but the REAL customers...the corporations buying the data you collect.”i

In the pursuit of what appears to be a bolstering of his argument, Kramer adds in the actual number

of people affected by the experiment, precisely “0.04% of users, or 1 in 2500” (Ibid.). As one

commentator John Morrow notes, “0.04% of FB users is hundreds of thousands of people”ii. For the

sake of argument, applying the numbers Kramer lists to currently available data, the equation would

look something like this: 1,440,000,000 (total monthly active users)28 x 0,04% (allegedly affected)

= 570,600 affected users. It seems detrimental to the downplaying efforts of Kramer that the very

numbers he releases as a form of reassurance so easily can be run to show that, in fact, what to

many people would constitute a significant amount of users – over half a million to be exact – were

potentially affected by the study.

The tendency to downplay agency is also present in Kramer’s formulation of the concept of

“hidden” posts, one of the concerns voiced by the many outcries following the publication of the

study. People worried about what they might have missed, given that the algorithm hid certain posts

and promoted others in the duration of the experiment. To this, Kramer says: “Nobody’s posts were

“hidden”, they just didn’t show up on some loads of feed”, to which the average respondent might

28 This number is drawn from the Statistic Brain Research Institute list, which was updated on September 20th 2015 and is accessible via http://www.statisticbrain.com/FB-statistics/

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say ‘Is that not effectively the same thing?’ (Ibid.). This is noted by commenter Chris Leeder, who

posts the following: “The difference between “hidden” and “they just didn’t show up on some loads

of feed” is pretty grey and would not be apparent to a majority of FB users”iii. The sign-off from

Kramer concludes what I interpret to be an overall strategy of downsizing and downplaying, but

also, peculiarly, of semi-apologising:

“I can tell you that our goal was never to upset anyone. I can understand why some people have concerns about it, and my coauthors [sic] and I are very sorry for the way the paper described the research and any anxiety it caused. In hindsight, the research benefits of the paper may not have justified all of this anxiety” (Kramer, 2014)

A semi-apology

As noted in the previous, there is a tendency throughout Kramer’s post to downplay agency, and to

diminish the significance of the events that have occurred. However, as the above quoted passage

from the text shows, there is also a presence of a different speech act – namely, what appears to be

an attempt at an apology. I label it a semi-apology, because of modifying features within it that are

significant enough to not warrant it an entirely apologetic function in the text. Observing the actual

wording Kramer employs in the ending of his post, a few of these modifiers become apparent. Most

notable, perhaps, is the following phrase: “my coauthors [sic] and I are very sorry for the way the

paper described the research and any anxiety it caused” (Kramer 2014, my italics). This warrants

the term ‘semi-apology’, given that Kramer is not in fact apologising for the act itself, but for the

way the act was described29. Also noteworthy is the phrasing that “the paper described” it, seeming

to leave the authors somewhat out of the picture. Kramer adds, “we didn’t clearly state our

motivations in the paper”, which seems to suggest that had the authors stated their motivations

(“concerned” about “negativity”, “never to upset anyone”) more clearly, people would not have

been upset as much.

The efforts towards diminishing the research methods and making them appear in a less grave light

corresponds with the apologetic differentiation strategy’s aim to “frame what has occurred in a way

that no longer portrays it as criticisable” (Lisa Villadsen 2009, p. 195)30. Kramer’s post seems to

29 Times Magazine journalist Jared Newman labelled this type of speech act a “non-apology” in his assessment of COO at FB Sheryl Sandberg’s statement about the study (Newman 2014). Sandberg’s “non-apology” goes: “it was poorly communicated (...) And for that communication we apologize. We never meant to upset you”, and thus in line with Kramer’s (Ibid.). I stick with the term ‘semi-apology’ given the presence of apologetic acts as I interpret them. 30 Villadsen’s chapter is in Danish. Any quotes from Villadsen employed in this thesis are provided in English by my translations.

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follow the formula that: “You think I did X (which is a criticisable act), but I have only done Y

(which might look like X, but is an entirely legitimate act)” (2009, p. 195-196). The strategy of

transcendence is also present in Kramer’s attempts to elevate the cause of doing the research in the

first place. This strategy introduces a more abstract perspective that leads focus away from the act

itself (2009, p. 196). As a whole, however, Kramer’s post contains elements from all four apologia

strategies – denial in the form of the implied denial that any real concern was warranted, present in

the downplaying of agency, and bolstering in the form of the efforts Kramer appears to put towards

establishing himself and his co-authors as calm, collected and careful researchers. The focus of the

post remains on the reactions the experiment caused – as Kramer finishes off his statement, this

becomes evident: “Those review practices will also incorporate what we’ve learned from the

reaction to this paper” (Kramer 2014, my italics).

(II) Ratios and the dominant term

From the previous it is obvious that agency is an important term in Kramer’s post given the invested

attempt to downplay it. Applying the possible ratios, I identify the most prevalent one to be

purpose-agency, and, thus, purpose to be the dominant term of Kramer’s post. While agency

analytically is interesting given the special position Kramer awards it through his efforts to make it

appear minimal, purpose is what Kramer posits as defining agency. It is the purpose, the “we care

about the emotional impact of FB” and “we were concerned [about] negativity”-theme of the post

that seems to function as a warrant for what was done. It is also through accentuating the beneficial

and almost altruistic purpose behind it all that Kramer appeals to his audience to heed his call to

calm, indirectly naming the reactions (not the actions) as the main issue at hand.

(III) Ideology

With purpose as the most featured term in Kramer’s post, Burke’s corresponding ideology of

mysticism is called forth. Although Burke provides a more religious and mystical philosophical

definition of mysticism, the general line of thought he presents has relevance in the case of Kramer.

Focus on purpose, Burke writes, marks “transition, flourishing when one set of public

presuppositions about the ends of life has become weakened or disorganized, and no new public

structure, of sufficient depth and scope to be satisfying, has yet taken its place” (1969a, p. 288).

While it is hardly the ends of life or lack of public structure being questioned and answered through

Kramer’s post, the public state of mind attached to such situations might not be too far off, given

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the strong reactions displayed in media outlets and the comment thread analysed later on. Kramer’s

post employs a strategy of transcendence, as mentioned above, and seeks to move the concerns of

his audience from one place to another, changing them along the way. In an attempt to lift himself,

his co-authors, and the FB brand out of the swamp of accusations and backlash they experienced at

the time, in Burke’s words “times of general hesitancy”, Kramer places emphasis on the ‘greater

good’, the “transcendent purpose” of it all (Ibid.). The fact that the post seems to miss its mark,

again given the conversation as it carries on in the comment thread of Kramer’s post, is an

important point in the concluding comparison of the findings of the analysis, and the onward

discussion in Part III.

4.3.2 Facebook and the missing act Moving on from Kramer to the post by FB on the official FB site, written by CTO Mike Schroepfer,

a different pentadic term becomes the focus of attention (or lack thereof). In analysing this artefact,

the existence of what appeared to be two simultaneous agendas was discovered, as well as two co-

existing pentads that went with them. Responding to the artefact, the following analyses both

pentads before concluding on the overall dominant term and ratio for the whole of the text. The two

pentads have been labelled “Regarding the experiment”, and “Regarding FB”.

(I) The five terms Regarding the experiment

The choice to put the run-through of this pentad first has, counter-intuitively perhaps, to do with the

fact that it is the most under-prioritised narrative in the artefact, but at the same time the one that

deals with the experiment itself, and what occurred during and after it. Scene is vaguely set as:

“Earlier this year”, and agent established as “we (...) at FB”, “FB does”, “We want (...) We will”

(Schroepfer 2014). Again, vaguely, the purpose of what was done, which have yet to be specified is

explained as such: “this subject matter was important to research”, and “We thought it was

important to look into this” (Ibid.). What is particularly noteworthy in this dramatic construct, as

mentioned in the above section, is the absence of an act. In the text, there is no mentioning of the

experiment itself, the methods, how the study was done, why that might be said to be wrong, or any

admittance beyond “[we] have taken to heart the comments and criticism” (Ibid.). It seems that the

audience is expected, in an enthymematical way, to fill in the gaps. The closest the post gets to a

defined act is the passive statement: “Earlier this year, our own research was published, indicating

that people respond positively to positive posts from their friends” (Ibid.). This sentence seems to

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subtly conceal any negativity connected to the experiment itself, or the motivations for conducting

it. It also does not address the further contents of the study, i.e. that negativity also made subjects

more negative – to some, a potentially more upsetting conclusion. Agency is explained backwards,

by noting what FB and the researchers “should have done differently” (Ibid.). Concrete examples of

the “things we should have done differently” are provided briefly by noting that “non-experimental

ways to do research” should be considered, as well as the need for “more extensive review

[practices]”, indicating the absence of the same in the case of the Kramer, Guillory and Hancock

(2014). All in all agent is the most explicitly present term of the five in this pentad, in the repeated

use of “FB”, “we”, and “we at FB”. However, given the absence of an act to tie to the agent, and

the almost absent agency, the articulation of an agent end up prevalent but without weight or

significant relationships to the other terms of the pentad.

Regarding Facebook

The other pentad present in the text by Schroepfer, and the one that occupies most of the text,

concerns FB and the actions that are being taken as a result of the vaguely suggested incident. The

act in this case is: “we’re making [changes] to the way we do research at FB”, and scene is set as:

“Over the past three months, we’ve taken a close look at the way we do research. Today we’re

introducing a new framework”. The agent, “We”, influences agency: “we’ve given researchers

clearer guidelines (...) we’ve created a panel including our most senior subject-area researchers (...)

we’ve incorporated education on our research practices into FB’s six-week training program”. The

purpose of this is described as: “improving the products and services we make available (...) in a

way that honours the trust you put in us by using FB every day” (Schroepfer, 2014).

The missing act

As one might note from reading the previous, the focus in both instances – Regarding the

experiment and Regarding Facebook – appears to be exclusively on FB. All the described actions

and happenings are set in a way that seems to centre them on the company. A quick count illustrates

this tendency: The word ‘we’ occurs 26 times, ‘our’/’us’ 10 times, and ‘FB’ 9 times in the text,

bringing it to a total of 45 references to FB itself. While this may not be generally uncommon in

corporate addresses meant to discuss internal practices, in this case the focus appears skewed given

the setting that FB did something to someone, and now answers to it. An articulation of the reader,

which is implied to be a FB user (“the trust you put in us by using FB”) and thus potentially ones

who were affected by the study, only occurs twice. This is noteworthy since one must assume that

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the Schroepfer statement is meant to at least to some degree respond to the widespread criticism

that followed the PNAS publication. The criticism came from an array of sources, but, as the further

analysis will illustrate, a significant response came from FB users themselves. While the statement

does say that FB “have taken to heart the comments and criticism”, the general focus of the text

remains not with the users, potential ‘victims’, or the reader’s possible concerns, but with FB.

Combined with the absence of an act, the lack of a description in FB’s own wording of what

occurred and why that might be said to be wrong, it leaves us with an artefact that appears to aspire

to comfort its reader and implied user (by noting the changed practices), but at the same time avoid

its reader’s objections (by leaving out their objections or concerns). In total, the FB statement seems

to have been created for a specific, and FB-centred, purpose – and like Kramer’s, it contains a semi-

apology.

A semi-apology

Although less prevalent than in Kramer’s post, the FB statement contains an attempt at a similar

apologetic stance. The focus, like in Kramer’s case, is not on what was done, but on how it was

communicated. In a wording much like Kramer’s: “we failed to communicate clearly why and how

we did it” – “it” being the study (Schroepfer 2014). The admittance of failure, however slight,

warrants the label ‘semi-apology’. Again the assumption behind the statement seems to be that the

reactions would have been nowhere near as strong had FB just made it more clear why they

conducted the study in the first place. This in turn seems to assume a set of common values between

FB and its users, which, had they been articulated, would have put people in the right mind to

accept the methods employed. As the analysis of the comment thread will develop on, this does not

appear to be anywhere near the case – in fact the general reaction to the study, Kramer’s post, and

to the FB brand in general, seem to be one of disbelief and mistrust. Simply stating more clearly in

the study why they did what they did does not seem to be a viable solution to the problem the

experiment presented FB – and its users – with subsequent to its release.

(II) Ratios and the dominant term Despite the vague articulation of purpose I identify the ratio most prevalent in the FB statement to

be that of agent-purpose. The attempt made in the text seems to be one similar to that of Kramer,

with a focus on transcending the concerns regarding methods (the absent act) in order to realise the

true value in a study such as the FB experiment. Agent becomes the dominant term, as it is the focal

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point of the text and the point from which all else is derived. All explanations starts and ends with

FB, and with their intentions, wants and needs. The upset users are minimally present in the

statement, and any warrant for their concern is left unmentioned.

(III) Ideology

Agent, being the dominant term, is attached to Burke’s ideology of idealism. Burke states that

“idealism lends readily into both individual and group psychology,” and links agent to idealism

through our different ways of conceiving the world through ourselves: “to approach the universe by

asking ourselves how knowledge is possible is to ground our speculations psychologistically [sic],

in the nature of the knower” (Burke 1969a, p. 172). Once again, Burke’s unravelling of his concept

of idealism is both wide and deep, reaching far into literature and philosophy in its explanations,

beyond what is relevant for the present purpose of this analysis. An important note, however, is the

observation that when we promote agent as dominating, we accentuate our own position and power

in creating the representation and idealistic perspective that we participate in. Idealism becomes “a

ground for action,” but “its essential feature is in its derivation from the attitudes of human agents”

(Burke 1969a, p. 175). It seems that FB is attempting to gather its audience around it by centering

the discourse on itself – something Burke labels “particularly serviceable when, unity having given

way to disunity, there is a call for unification” (Burke 1969a, p. 173). In the FB case, the call for

unification is related to the public demanding responses – like the one Kramer posted to his FB

wall. The following analysis of the comment thread begins to answer whether this “call” was

answered effectively.

4.4 Rude awakening: Facebook users vs. Kramer It is fair to assume that Kramer’s post was created to counter some of the allegations made against

the experiments conducted, the research methods, and the researchers (“A lot of people have asked

(...) I wanted to give a brief public explanation”, Kramer 2014). However, if the post was intended

to ward off further questions, or meant to answer any remaining doubts in its audience, the target

seems to have been missed, as the following will show. One could also interpret this apparent

discrepancy between the statement provided and the statement desired (as evident in the comments)

to be symptomatic of the aforementioned knowledge gap between FB as providers and

commentators as users, on both their sides of an understanding of algorithms. What follows here is

a brief explanation of the method employed in my analysis of the comment thread, given that the

treatment of this artefact varies from the others.

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4.4.1 Method

The responses to Kramer’s post from FB users vary in nature, but certain commonalities are

detectable. Before proceeding to the pentadic analysis, I offer a textual analysis of examples from

three categories of responses in the comment thread. This functions as an initial reading of the

artefact, in order to qualify observations made later on as I proceed to the pentad and the further

discussion in Part III. The three common categories of responses are labelled: the scholar, the

ethicist, and the outsider. These categorizations constitute the first of two steps taken in my textual

analysis of the comment thread – the second step being the pentadic analysis. Identifying the three

common positions within the thread, I printed off the comments to stabilize the artefact (Hoff-

Clausen 2008), and read through the thread in its entirety several times with the aim of formulating

common positions manifested throughout it, and determining how prevalent the positions were in

relation to each other. This way of analysing an artefact consisting of comments is preceded by

Jakob Linaa Jensen in his book “The digital democratic dialogue”, where Jensen groups comments

by common profiles or ‘personalities’, such as ‘the humorist’, ‘the paranoid’, and ‘the moderator’

(2007, p. 44). Danish rhetorician Rasmus Rønlev also identifies the practice of creating common

categories to group comments in as a useful tool when dealing with threads (2011, p. 141-142).

Although Rønlev analyses a significantly larger sample size than I, his reasoning behind

approaching comment thread artefacts are equally relevant: One must consider, for each comment,

what is being commented on, which topic within that is being addressed, and what attitude towards

it is evident (Ibid.). While I do not specify each of these questions explicitly, they directed the

creation of the three categories that follow. In terms of the quantity of comments analysed, the total

amount of entries following Kramer’s post is currently at 160 (Kramer 2014). As mentioned

previously, 91 made it into the categorization process. The comments left out of consideration were

either marked by vulgar language limited to a single expression without further context or

argument. The criteria for considering comments for analysis were that they, after the initial

reading, were perceived to carry value towards the aim of the analysis of this particular artefact,

namely that of mapping general reactions from FB users. While vulgar language of course

constitutes a reaction in itself, I was interested in the narratives people created around the incident –

how did they reconstruct the particulars of the case, and with what effect?

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4.4.2 Introducing the categories

Even though grouping individual opinions in the manner described above simplifies the nuances

present in each of them, it is helpful in making evident the general positions assumed by individuals

debating the FB case. The categories – the scholar, the ethicist and the outsider – are meant to

underline the presence of different positions before I define, based on my reading of the artefact, the

predominant depiction of the five terms of the pentad, dominant ratio and ideology. The three

categories are introduced in an order corresponding with their quantitative prevalence in the

commentary track – the scholar being the most typical type of response. It is remarkable that any

substantial debate concerning the role of algorithms is almost exclusively detectable in the least

frequent type of response: The outsider, as well as in ‘the outsider’ artefact category. I interpret this

to be symptomatic for the public conversations we have surrounding such questions as those that

faced people after the FB experiment – the particularities are left to experts and tech interested, and

the majority end up upset but uninformed. While the scholar category represents arguably

warranted concerns about the lack of academic standards in the methodology of Kramer, Guillory

and Hancock’s study (2014), the ethicist category contains objections that are, when one is

somewhat aware of the nature and workings of the News Feed algorithm, obsolete. Some of the

practices being criticised in the particular case from 2014 are so ingrained to how FB works all the

time that objecting to them, because they suddenly become evident, seems to mark the lack of

understanding of the site more than it marks the site itself. This, again, marks the presence of a

significant knowledge gap. It creates a vantage point for companies that profit off of data trade that

their subjects are unaware, and while getting a free service in exchange for your personal data might

appear a fair deal to some people, it is nonetheless a choice that should be made knowingly. As the

categories, and particularly the ethicist, show, this is far from being the case. This is what

constitutes the ‘rude awakening’ employed in the headline of this section. Because it is not only

Kramer and FB that faces an awakening in the form of the continued questioning and dissatisfaction

from their users. It is also the users themself, facing what many of them did not know to be the

workings of the site they frequent most.

4.4.3 The Scholar

The most frequent accusation directed at FB after the release of the study concerns the

methodological considerations and method employed in it. Even though Kramer addressed this

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point in his statement, he did so somewhat dismissively31. The statement did not seem to ward off

further questioning, as news outlets following the publication of the study focused almost solely on

this point (ABC News 2014; BBC News 2014; Goel 2014; Meyer 2014; Penn 2014; Schaefer

2014). It also carried over into the commentary track following Kramer’s post, with questions

concerning this topic being the most prevalent within the comments. The FB users asking about this

particular point approach it from what can be identified as a scholarly point, hence the headline of

this section: They interact with the information presented by Kramer as would academics, fellow

researchers or scientific critics. To imitate Linaa Jensen’s (2007) profiles, we might name the

people belonging to the scholar category as ‘peer-reviewers’. Comments assigned to the scholar

category are interpreted to participate in the conversation from this standpoint given the content of

their inquiry or statement, the tone of voice they adapt, or the authority they claim for themselves in

the context. The following characterize their responses.

Overall, and not just in the scholar category, it is worth noting that the general atmosphere in the

comment section is critical of FB and the research. The tone of the comments following Kramer’s

post spans the entire range from applauding over neutral to heavy criticism bordering demonization

of FB. However, few comments applaud FB or the research(ers), and those that do are hard to

perceive as anything more than random comments in passing, such as Abhas Gupta who posts:

“Fantastic response, Adam. Well done”iv. The response from a frequent commenter in the thread,

Leah DeRose-Wilson, immediately questions Gupta’s praise: “Response? It addressed exactly none

of the issues..”v. An example of a more elaborate and still positively worded comment is the

following posted by Dale Sheldon-Hess:

“Fascinating/useful research, but I think I agree with the people asking for a better version of informed consent. “You have been randomly selected; click to participate!” You could even pay people in not-showing them ads.”vi

This is also an example of commentators providing suggestions and advice as a part of their

address, which is not uncommon in the scholar responses. The neutral questions are, like the

applauding ones, few, but present: “Did UCSF’s or Cornell’s Institutional Review Boards approve

the study?”vii. Many comments, particularly in the scholar category, border between neutral and

critical. They keep a neutral if not jovial tone of voice, but contain formal, academic points of

criticism as unrelated to their personal experiences or concerns as possible. An example of such a

31 See ‘4.4.2 Kramer: downplaying agency and almost apologising’

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comment, or even commenter, given her active participation in the thread, is evident in the case of

Leah DeRose-Wilson:

“True, I liked that review as well, I don’t 100% agree with it – but while I do agree that the research doesn’t violate any laws. I do think an IRB should have been required (it was not preexisting data....). I don’t really think FB did anything out of the ordinary with the research, but I do think PNAS violated their own ethical standards by publishing it (and they appear to agree – since they published because it had an IRB that it didn’t actually have).” (Comment by Leah DeRose-Wilson, 30th June 2014).

Although the wording and grammar of this comment are marked perhaps by DeRose-Wilson’s

eagerness to write it and post it quickly, it reflects a general tone of voice that is centred on external

issues and formalities that can be questioned, rather than personal attacks or anything of the sort. It

weighs pro’s and con’s, and does so in what appears to be a calm manner, focused on procedures

and standards. Furthermore, as DeRose-Wilson is an example of in the Kramer-thread, there is a

tendency in this category for individual commentators to return to the conversation and stay active

over extended periods of time – commenting numerous times within the same day, and over several

days. I interpret this to imply that there is a genuine interest in the questions raised by the FB

experiment. Few ad hominem’s can be detected, even though the post the comments are responding

to is by Kramer himself, making him an easy target. Cara Ostomel posts an example of a

moderating comment drawing others’ attention to this possible pitfall in the debate:

“And Donald, I think a lot of people are bothered by the methods, and that’s certainly a great conversation to have. I think most studies in academic journals could benefit from open discourse about the methods and analyses and ways to improve. As long as we’re criticizing the research and making suggestions for ways it could have been done better and could be improved, rather than simply bashing the authors”viii

Another reoccurring phenomenon in the scholar comments is relatively long posts, and at times

several of them in a row, creating what could almost be labelled a sort of blog post format within

the comment sectionix. Perhaps the tendency of commentators giving this kind of substance to their

posts can be said to be related to the scholarly, academic thematic sphere that they are participating

in indirectly with their posts – perhaps the development and unwrapping of argument typical of an

academic text is carried across to the genre of comments.

The most significant characteristic of comments assigned to the scholar category is their overt focus

on procedure. Their main allegation against FB does not concern the fact that the experiment

manipulated emotions, but that the academic standards for published research was not met:

“I think that what people find especially upsetting about this is not that we had some trust in fb that has been violated ( haha), but rather we’re upset to see a large company (with tons of personal

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data) totally disregard the normal ethical standards used for PUBLISHED research (and get away with it)”x

What is interesting to note is that, as the ethicist category will show, a group of users barely second

in size to that of the scholar was in fact upset by what they interpreted as a violation of trust. As

DeRose-Wilson cries procedure, and argues that it is the fact that the research was published that

upsets others, she accentuates the existence of a knowledge gap: Her comment already assumes that

FB users are sceptic towards FB, the same attitude of “public mistrust” recommended by Hinman

(2008). However, as the ethicist elaborates on, this appears to be far from the case, given the

emotional uproar that followed the study. The overall argument made by the scholar seems to be

that “We are not angry about what you did, we are angry that it got published in an academic

journal”. In a way the scholar follows the logic of Kramer and Schroepfer when they semi-

apologised for the way the research was received rather than the research itself. The scholar

dismisses playing the part of the victim in relation to FB, and instead assumes an institutional role

on an equal level with the FB researchers as they review their work as peers – and finds it

inadequate.

4.4.4 The Ethicist

The second most prevalent position assumed by commentators following Kramer’s post is labelled

the ethicist. It is a position from which concerns of ethics, morals, and socially responsible

behaviour are given priority over, for example, the academic interest in methodology that was

prevalent in the previous. A comment assigned to the ethicist category might still be questioning the

study’s methodology, but does so from a different point of entry, namely one of ethical evaluation

and moral judgement. The primary argument of the category is that the FB experiment, in changing

FB users’ News Feeds, have violated the right of humans to sign an ‘informed consent’ agreement

prior to any experiments being conducted on them. More specifically, the category also concerns

itself with the alleged harm the experiment caused people who are suffering from mental health

disorders such as depression or bipolarity. This particularly concerns the fact that the experiment

suppressed ‘positive’ content and promoted ‘negative’ content with some users, which the average

ethicist believes to have had a severe effect on mentally fragile individuals. As such, the ethicist

category presents some of the most obvious examples of the aforementioned knowledge gaps given

the nature of the accusations made against FB and its research: Through their reactions, they reveal

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just how little they are aware of the everyday workings of the News Feed algorithm, and of FB in

general.

The ethicist shares certain characteristics with the scholar category. There is a significant amount of

commentators from this category that return to the conversation, and stay active over extended

periods of time. There is also, like with the scholar category, a tendency for commentators to post

longer texts, even spanning several comments, when making their points. Unlike the scholar, the

ethicist grouping displays a greater tendency towards adopting a subjective, highly critical,

emotional tone of voice in their comments. Correspondingly, there is also significantly more

frequent use of emotive typographical expressions such as capital letters and exclamation points.

An example of all of the above characteristics are embodied in commentator Susan Liên Whigham,

a FB user active in the thread from the beginning to the end, replying to other comments, posting

long statements and employing various strategies in making her concern be known:

“Attention Adam Kramer, if you’re listening. Just because people aren’t affected enough to be commenting about it in their status posts doesn’t mean they’re not being affected, or that they’re being “minimally affected”, by seeing only negative posts in their feeds. People suffering from severe depression or on the verge of suicide could have been very adversely affected, and you would never know because you didn’t bother to find out first. More importantly, the impact of knowing that someone can be so insensitive as to experiment with your emotions without asking their permission first is very dehumanizing. Thank you for at least (and at last) being forthright about it.”xi

This comment also contains a personal appeal to Kramer, something that occurs primarily in the

ethicist and the outsider category. Where Whigham’s post is an example of what could be labelled

gatekeeper-rhetoric, where the commentator assumes a position of protector over the potential

victims of the experiment, the ethicist category also contains comments from users assuming that

victimized role:

“I am not a scientist. I do not have a phd. Most of this thread is a foreign language to me. However, the realization that FB could have been manipulating my Newsfeed in some way and using me for a study that I wasn’t aware of or didn’t approve of...well it pisses me off. And thanks to FB’s lame ass privacy features now most of my “friends” will probably know too...just because I commented here. Great job FB!”xii

This comment represents the unawareness of the category in general well: The anger and surprise is

directed at 1) the manipulated News Feed, and 2) the fact that FB performed a study involving users

without their knowledge. Overall the reactions of the ethicist FB users mirror the reactions that

were present in the Eslami et al study (2015) – anger and surprise dominate the category, seeming

to link the state of unawareness to the concerns expressed. As Eslami et al noted, once users got

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more familiar with the workings of the site (and the algorithm), their satisfaction levels went back

to the way they were before the users gained awareness. As such I see the majority of the ethicist

responses to be examples of the same kind of ‘unaware user’ reaction that was observed by Eslami

et al (2015). The anger and surprise element of the responses is also detectable in the use of coarse

language, which is more common in the ethicist posts, perhaps given the personal attachment and

identification between one self and one’s FB account, and what the experiment is perceived to have

done to those. Irony and humour is employed sporadically throughout the comments to emphasize a

message of disagreement and discontent. In some cases, however, the reactions of users identifying

with the role of the victim display more anger than surprise, and become more emotionally

immediate, as appears to be the case in the following comment:

“I mean...why not just fuck off, and let us see whatever our friends post? if i don’t like that person’s post, I’LL decide whether or not i want to see more of them or not. not you, FB. quit telling me what’s good for me, YOU DON’T EVEN KNOW ME!”xiii

This adverse reaction to authority, and focus on the power and authority of FB, is common for the

ethicist category’s responses. Within the category there seems to be unanimous agreement that FB

has violated the rights of the individuals included in the experiment, and that this willingness to

sacrifice the right of choice on behalf of others somehow show the ‘true nature’ of FB (“Thank you

for at least (and at last) being forthright about it,”xiv). This true nature is interpreted to be one of

manipulative, purely capitalistic intent with little to no regard for the users that are being traded as

commodities. This notion traces back to Sundar and Marathe’s (2010) observations mentioned in

the beginning of this thesis that we tend to be gullible about potential threats to privacy as long as

we are not explicitly informed about them – however, once we are made aware of the fact that a site

is tracing our use, or even profiting from it, we become remarkably more cautious and hesitant to

continue using it. What seems to be completely left out of the ethicist comments is the fact that the

News Feed algorithm has always been performing the kind of prioritization and curation of posts

and information that is causing all the sudden anger. There is little to no mentioning of algorithms

at all, and there appears to be no real understanding of the workings of the News Feed prior to the

news of the study. The ethicist as a category, thus, becomes an example of the aforementioned

knowledge gaps, as they enact the same emotional reactions as the participants in the Eslami et al

study (2015), and attack FB for manipulating their News Feeds even though this has been a well-

known reality for other groups of users all along. The real issue at stake then appears to be the lack

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of information the average user has of what takes place algorithmically in the large-scale media and

sites that we frequent in our everyday lives.

4.4.5 The Outsider

The final and least frequent category identified has been labelled the outsider category. The name

the outsider is given for two reasons. Firstly, the responses assigned to the category assume an

outsider position towards not only the experiment, but also the other commentators. Secondly, their

responses contain a remarkably different tone of voice, one that either tends to distance themselves

from the sentiments of their co-commentators, or one that performs a meta critique of what could be

called ‘code of conduct’ in the thread. In total, comments assigned to the outsider display different

roles throughout the thread, prevalent ones being that of moderator and meta-critic, but certain

common characteristics are identifiable across the category. Most remarkable about the category is,

in the context of the other categories, that it is the only one that discusses the role of algorithms in

the FB experiment, and in general. This leaves us with the final role that the outsider responses tend

to display a presence of: that of the expert. Although the roles just named will not be pursued per se

in the following, they function well as pointers for the general profile of the outsider category, and

will be used to suggest the positions assumed by commentators assigned to it.

In the outsider category, the main address is directed at other commentators. There is a tendency for

the outsider to articulate surprise and even disbelief at the outrage present particularly in the ethicist

comments. The outsider positions himself on the sideline of the argument between FB and the

majority of FB users, and ponders the behaviour on both sides. A common response to the uproar is

present in a comment by outsider Fred Zeleny:

“I really don’t see why people are freaking out about this. FB has manipulated which posts you see in your feed for years (maybe a decade). The only difference this time is that they published a paper and advanced psychological understanding in the process.”xv

The outsider is surprised not by the experiment or its methods, but by people’s surprise and

reactions to it. Their comments tend to contain variations of “did you not know this was

happening?” and a general surprise at what they conceive to be a lack of knowledge and awareness

present in the majority of the comments in the thread. There are also displays of self-reflection and

the realization that not all users are equal – some of the outsider commentators acknowledge their

privileged position in understanding the media they are partaking in:

“I have to admit, my first reaction to the controversy was similar to Fred’s: FB manipulates the feed all the time, so why are people so upset about this? (...) Upon reflection, though, I think that’s

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very much a “sophisticated user” reaction. Most people are not terribly aware of How Things Work and I think that we, as technologists (and researchers) have a responsibility to understand that.”xvi

It is interesting how this commentator labels his own immediate response a “sophisticated user

reaction”, thus hinting at the existence of different tiers of users. This is one of the most to-the-point

articulations of the knowledge gap that seems to exist between the users, the providers and the

outsiders in the constellation of the FB case. The same commentator, Michael Higgins, proceeds:

“I think, as a society, we’re looking toward several futures: (1) companies and governments could get more careful and conservative about how we use data; (2) individuals could get better educated about what is possible and what is common practice; (3) we can continue to muddle along as we have been: knowledge is power, and most people are ignorant. I hope we aren’t doomed to (3).”xvii

Again, Higgins presents a key point in the discussion of the different reactions present in the

comment thread following Kramer’s post. The outcry of the many, present in the scholar and the

ethicist category, mainly concerns academic standards not being met, if we approach it

quantitatively. However, qualitatively, there is a substantial underlying (and at times overlying)

current of contempt towards the doings of FB running through the comments. Following Higgins,

there seems to be a lot of commentators who were previously unaware of the workings of a site they

frequent often, if not daily. The capabilities of FB, administered through the News Feed algorithm,

were not in the forefront of people’s awareness, but as they are presented with it and realize it, they

react strongly. This reaction marks their need for being “better educated about common practice”,

as Higgins puts it, which in a way reaches back to the comment by Jeff Hancock, one of the authors

of the FB study, who remarked that perhaps an educational component was necessary in people’s

interaction with FB (Hancock 2014). These observations are important because they make evident a

blind spot in the user/provider relationship: The users do not understand the media they are a part

of, and the providers fail to realize that this lack of understanding presents a potential issue for

them. On both sides there is a lack of understanding of the other, - a knowledge gap between them -

, which might explain why Kramer’s post initially seems to miss its mark: It fails to address the real

issue at hand, which could be said to be the overwhelming amount of uninformed and unaware

users becoming more informed and more aware – and thus, more concerned, and in need of more

answers. Within the category, there are displays of hybrids between the scholar and the outsider,

with commentators addressing Kramer and explaining, on behalf of other users, what answers might

be more reassuring than the ones already provided:

“Adam – what might be helpful for folks is some kind of statement about the extent of the manipulation. e.g., “the average participant in the study had 2.3 posts hid (vs those they would

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normally see) during the course of the 7-day study.” I don’t know what this number is, but my sense is from the stats you report in the paper that it is probably fairly small. I think that would help people get a sense of the magnitude of the manipulation.”xviii

This is another example of an articulation of the difference between the outsider and the ethicist –

Nicole Ellison addresses Kramer, a representation of FB in that context, as a peer, and suggests a

course of action based on what “people” would find helpful. Other commentators resort to more

direct and concise statements, without any evident elements of interaction or dialogue, but still with

what appears to be an indirect address aimed at the people who were shocked by the FB

experiment:

“Fact #1: All digital media companies run thousands of experiments a year to maximize usage or revenue. Fact #2: Many of these experiments will affect users’ emotional states, intentionally or not. Fact #3: The ONLY difference with this experiment was that it was published as basic science (i.e., the public gets to find out about it).”xix

The examples presented in the comments provided in this section make evident the gap between not

only users and providers in a case such as FB, but also the role assumed by privileged

commentators as they try to educate their fellow users. While drawing greater conclusions about the

average awareness of FB users based on entries in one comment thread is a questionable basis, the

outsider being the least common type of response in the comment thread seems to hint at the fear

Higgins articulated: “knowledge is power, and most people are ignorant”.

(I) The five terms The three different common categories of comments in the thread following Kramer’s post present

different possible ways of filling out Burke’s pentad. The aim here, however, is to distil the most

prevalent reaction pattern into the five terms, and then move on as prescribed. Given the low

occurrence of the outsider category in the thread, I have chosen to save the important points made

by those commentators for later. The artefact labelled the outsider, which will be analysed after

this, contain very similar sentiments to those present in the comments (hence the double use of the

outsider), and their observations make up a main part of the discussion in Part III.

The prevalent pentad in the comment thread portrays the FB case as follows. Scene is set to be a

week in January 2012, and agent as Kramer, Guillory and Hancock, as well as FB. However, the

comments appear to interpret Kramer, Guillory and Hancock as extensions of FB, making the site

the overall agent. Act and agency somewhat melt together in the comments, and can be determined

as “FB has manipulated which posts you see in your feed”xx, in order to “to experiment with (...)

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emotions without asking (...) permission first”xxi. The general lay-out of the act and agency is

summed up in the following comment’s portrayal of the situation: “FB (...) have been manipulating

my Newsfeed (...) and using me for a study that I wasn’t aware of or didn’t approve of”xxii. The

purpose of it all appears to be commonly understood as “to maximize usage or revenue”xxiii.

(II) Ratios and the dominant term The dominant ratio is found in the act-agency relationship, making act the dominant term identified

for the whole of the comment thread following Kramer’s post. It is ‘what has been done’ and ‘how

it was done’ that dominate the content of the comments, and ‘what has been done’, or act, is the

most criticised. It is also the aspect evoking the most emotional and ethically centred reactions from

commentators. This tendency reflects what the outsider category points out, namely that a majority

of commentators previously were unaware of some of the basic functions of FB in terms of

algorithmic sorting of information in the News Feed, and data collection from users as a part of the

business model that is FB. The many reactions to the fact that a study like the FB experiment took

place mark the lack of knowledge that exists about one of the giants in social platforms, and about

the concept behind social media sites altogether. This lack of understanding is what the following

artefact, the outsider, is surprised by, and tries to address.

(III) Ideology

A focus on act brings forth Burke’s ideology of realism. Burke provides an example that is fitting

for explanatory purposes: “Socrates, approaching the world as a moralist, necessarily considered it

in terms of actions. Reality, he said, was the power to act and be acted upon” (1969a, p. 230). It is

by giving the actions taken by FB prevalence that the users and commentators end up passing moral

judgment on the company as a whole. What Burke labels an “action-passion grammar” dominates

particularly the ethicist comments, wherein “action organizes resistant factors, which call forth the

passion” (1969a, p. 264). The articulation of FB’s misdeeds give rise to a conversation centred on

the rights of the users as human beings, and a at times heated debate on the sanctity of privacy and

personal information. Once again, the point being missed seems to be that the very basis for the

existence of a platform like FB is that users relinquish personal data, which is then used by FB

itself, but also traded as a commodity to third parties. This observation and more like it are present

in the following artefact, consisting of two selected responses to the situation from the tech-

community.

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4.5 Outside the system: Tech-community responds The third and final position relevant to a further discussion of knowledge gaps in our increasingly

digitalized society is that of the tech-community. As have been made evident throughout the

analysis of the comment thread, certain commentators assumed the roles of moderators, meta-critics

and experts in displaying their technological capabilities, or at least their more developed

understanding of the workings behind FB and the algorithmic construction of the News Feed. This

understanding gave them a privileged position in relation to the controversy, as they were able to

put the experiment into a context wider and more detailed than that of the average commentator,

who was shocked to discover the actions made possible by algorithmic media such as FB. The

outsider commentators were also the only ones observed to be discussing the role of algorithms in

the grander scheme of things, and generally approached other commentators with a call to calm, and

an attitude along the lines of: “Didn’t you know?” The following pentadic analysis considers two

examples of this position from outside of the FB interaction, in order to accentuate the overall

presence of the sentiment present. The examples consist of a blog post written by Laura Phillips

from State of Digital, a knowledge platform primarily created for digital marketers, and an article

entered in Massachusetts Institute of Technology’s (MIT) Tech Review written by Will Knight. The

two texts are interpreted to be representative of a general position assumed by tech-savvy

bystanders to the uproar caused by the FB experiment.

In her blog post, named “FBs Experiments & Why We Shouldn’t Be Surprised”, Phillips takes her

readers step by step through her reasoning of why she is not upset by the FB study – and why we

should not be either:

“FB is a business. When you sign up, as 99% of us did, without reading the Terms & Conditions because they were long and there was a LOT of small print, we sold our souls [to] the FB Marketing Overlord. When we merrily jotted down every last piece of personal information and clicked ‘Next’ to confirm each one, did we give a single thought as to how it would be used? (...) WHY did we think FB was created? What were they going to do with all that information?”(Phillips 2014).

Phillips addresses the unawareness and the lack of reflection that was also present in the outsider

comments from the Kramer thread. She articulates the knowledge gap, the missing links in people’s

minds between the service they are receiving from FB, and the business that is being run in the

other end. Phillips goes on to note that “seeds of privacy issues were there from the start”, but that

“when we signed up we allowed this, we agreed to it” (Ibid.). The issue is put to bed with Phillips

noting, “I will always come back to the point of ‘personal responsibility’. You are responsible for

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your choices, no one else. [If you] don’t like it, leave FB” (Ibid.). Placing it in a larger context of

the Internet as a whole, Phillips adds a quote by OKCupid creator Christian Rudder from his

comment on the FB study:

“...guess what, everybody: if you use the Internet, you’re the subject of hundreds of experiments at any given time, on every site. That’s how websites work” (Ibid.).

Knight makes similar points to Phillips, and his headline reads “This Headline Is One of Many

Experiments on You” (Knight 2014). Knight opens his text with the statement: “On your way to

this article, you probably took part in several experiments (...) whether you realize it or not, the

Web is already a gigantic, nonstop user-testing laboratory” (Knight 2014). Also Knight is quick to

name the knowledge gap between providers and users of Internet products, as he goes on to note, “it

(...) seems that few people realize quite how much of it is going on” (Ibid.). Like the outsider

comments from the Kramer thread, Knight assumes a privileged role of educator towards his

readers, and explains: “companies with large numbers of users routinely tweak the information

some of them see, and measure the resulting effect on behavior [sic] – a practice known in the

industry as A/B testing” (Ibid.). While Knight’s article is written from the point of view of an

outsider to the FB controversy, he importantly notes, in a visually separate textbox next to the

article itself, “Why it matters: Online services can shape our perception of current events by

tinkering with what they present to us” (Ibid.). In these ways, Knight articulates his own and others’

concern by the realization that so few people are aware of what goes on daily when they interact

with Internet products, as well as the impact this unawareness can have on our way of perceiving

the world.

(I) The five terms

The interesting part about the tech-community’s response to the situation versus the users’ response

is that they have a very similar way of filling out the pentad’s individual elements. Agent is

understood as FB: “FB had engaged in a large scale test” (Phillips 2014), “FB [published] a study

on the way negative emotions can spread across its network” (Knight 2014), and act as the

experiment itself, also evident in the quotes just listed. Agency is more vaguely described, but still

captures the essence of what ends up being the critique in the comments: “The study (...) involved

showing some people more negative posts (...) and then measuring how this affected their behavior

[sic]” (Knight 2014). Purpose is portrayed in a different light than in the comment thread: “FB

wanted to see how people reacted in this environment to positive and negative emotions” (Phillips

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2014). However, the biggest difference between the two accounts, as I have generalized them

through the pentadic analysis, is present in their definition of scene. For the outsider, scene

becomes much more than a given time, date or event at which something took place. Scene, in this

context, is understood as the wider context in which Internet businesses such as FB are a part. It is

an ongoing, developing field, and one that determines the actions and purposes within it. The scene

of technological developments contains the other terms of the pentad, and this grants a different

perspective and framing altogether of act, agency, purpose and agent. Where scene to the comment

thread artefact is set as nothing much more than the time where this particular instant occurred, the

outsider localises this act as one that exists on a scene containing many similar ones. The only

identifiable difference, in the view of the outsider, is that this experiment, unlike many of its

counterparts, was published.

(II) Ratios and the dominant term

The dominant ratio for the outsider category is scene-purpose. The defining difference granting the

outsider a more privileged position of perception in the overall conversation is the widened horizon

on which they locate the FB experiment as one of many of its kind. Purpose is acknowledged as

potentially questionable, but is at the same time recognised for its commonness within the business

of social media in general. The outsider category, both in the FB comments following Kramer’s

post and in the two selected texts introduced in the previous, thus, display their ability to

comprehend the FB case as a part of a greater whole by focusing on the overall genre it is a part of:

The business of the Internet.

(III) Ideology The term scene is attached to Burke’s ideology of materialism (1969a, p. 128). As mentioned

before, Burke’s explorations of the philosophical and literary counterparts to his philosophical

languages, as he names his ideologies, are too far-reaching to include in their entirety. In Burke’s

own words, I aim for these paraphrases of Burke’s exceedingly more complex definitions to be

“representative rather than exhaustive” (1969a, p. 169). For present purposes it is sufficient to note

that materialism with Burke is understood to signify context, which ties in well with the

observations made in the above sections. Burke writes that scene and the corresponding materialism

underline the line of thought that we are “parts of a non-personal whole (just as, shifting the stress,

we perish by reason of our natures as parts of a whole)” (1969a, p. 150). He goes on to note: “This

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contextual emphasis is always uppermost” (Ibid.). Burke’s chapter on scene stresses, “particularity

is grounded in a total context, and thus is to be understood in terms of this total context” (Ibid.).

This appears to be what the artefacts belonging to the outsider category are doing, by trying to

explain to their fellow FB users and readers “How Things Work”, as one comment following

Kramer’s post put it.

4.6 Comparison of findings The analysis of the three overall groups of artefacts surrounding the FB case shows how differently

the particulars of the situation are portrayed and how little the different groups actually seem to be

communicating with each other. Relating the findings to the first part of this thesis, it might appear

that what sets the individual rhetors apart is in fact their level of awareness when it comes to the

workings of algorithms. From the point of Kramer and Schroepfer, their awareness of the existence,

purpose and function of the News Feed algorithm seems to make them assume that the otherwise

concerned FB users will calm down once they receive an apology for the way the study was

communicated. They seem to assume that what is concerning people is not so much the fact that the

study happened or that the News Feed can be changed to fit purposes out of people’s reach, but that

it was presented to them in a somehow inappropriate way. The semi-apologies made by both FB-

parties illustrate this gap, as they focus on almost anything but the algorithmic character of the

News Feed. The continued reactions in the comment thread of Kramer’s post, as well as the overall

media attention that the publication of the study received, make it evident that it is not the way the

study was communicated that upsets people. It is the realization that these types of studies even

occur and the sudden awareness of the News Feed being algorithmic that the publication faced FB

users and others previously unaware with. From the point of view of the FB users, as they are

present in the comments, the FB study presents several issues – and three main ones, as identified in

the general positions assumed by people posting in the comment thread. In the scholar there are

concerns about academic standards, which, although relevant as a debate point, do not spark as

strong emotional reactions as the concerns about privacy, exploitation, and manipulation present in

the ethicist. For the outsider, it is the level of unawareness he observes in his fellow commentators’

inputs that concerns him. Finally, the last artefact category, also labelled the outsider, echoes the

concerns of the commentator position of the same name. There is disbelief expressed at how little

so many people knew about one of the most frequented social platforms of the Internet, and at the

same time recognition that this is a privileged user reaction. These are the distances of

understanding, the knowledge gaps that exist between providers, users, and tech-savvy bystanders

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in the FB case. However, I believe that the knowledge gap and the obvious differences of

perception that can be observed in this particular case have wider application and relevance –

particularly concerning political polarization, our behaviour on- and offline, and the enactment of

rhetorical citizenship in 2016.

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5.0 Part III: Discussion The analysis of the rhetorical responses to the publication of the FB study from 2014 show the

existence of knowledge gaps between providers, users, and tech-savvy bystanders to the incident.

The rhetorical nature of algorithms seem almost heightened by the different reactions – the blind

spot the providers have for the level of awareness of their users, the cries of manipulation and

shadow play from the users, the disbelief of the tech-community. They all seem to somehow

illustrate the fact that algorithms are not, in Hess’ words, “objective” and “absent of human

interference” as they might at first be perceived to be (Hess 2008, p. 45). People react to them as

they would to propaganda or the likes. It was exactly the manageability and changeability of

algorithms and their underlying assumptions combined with their influence that made them so

rhetorically interesting to me in the first place. In this discussion, I mean to argue that the

knowledge gaps between particularly providers and users of platforms such as FB have an impact

on the enactment of rhetorical citizenship for the average user, as they interact with technology that

they do not understand in the first place. I believe that a user’s level of algorithm awareness affects

her ability to make and communicate informed decisions. However, not everyone agrees that

exchanges made on FB can be taken as representative of an unfolding of public debate and

rhetorical citizenship in the first place. Since I want to argue that the FB case is representative of a

greater tendency, it seems important to first address this counterpart to my assumptions. Therefore,

my first argument in this discussion concerns whether or not we can take utterances on sites such as

FB to be indicative of public opinion and tendencies beyond online life as an isolated concept -

which I believe, to a certain point, we can.

5.1 Facebook: An echo chamber or a social pond? In a recently published article on the popular Danish website KForum, an online platform for

communication professionals in Denmark, Professor of Media Studies Stig Hjarvard warns

practitioners and academics of taking utterances posted on platforms such as FB to bear any

significance towards an assessment of public opinion (Hjarvard 2015). Hjarvard’s point is that on

FB, being a social platform, users strive towards being recognized for their views – and if they

sense that their views go against the main stream opinion, or even if they are just unsure of the

views of others seeing their posts, users will simply not post anything. Hjarvard roots this point in a

recent Danish study that surveyed users of social media about their willingness/hesitance to post

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political content to their profiles, or comment on potentially controversial material (Ibid.). The

study found that a majority of users are more concerned about being perceived in a certain (positive

or favourable) way by their FB friends than they are about expressing their earnest opinions on

political or current events (Ibid.). In other words, people will rather stay quiet and keep up face than

engage in a debate that could possibly taint their social profile on FB. This is why, in Hjarvard’s

words, it might at times appear as though there are political debates taking place on FB – when in

fact it is the utterances of the few that form them, while the majority of people shy away from

potential damage to their online personas. In short, this is why we should be hesitant to take FB

utterances to have any relevance towards an assessment of public opinion: They are a skewed

image.

Hjarvard dismisses the idea of an echo chamber, a concept I used earlier to describe one of the

possible effects of algorithms sorting our information based on an underlying assumption along the

lines of “likeness is good”. Instead of the metaphor of an echo chamber, Hjarvard offers that of a

“social pond” around which users gather to make exchanges of politically insignificant and

unthreatening, often humorous, character (Hjarvard 2015). However, Hjarvard adds in a notice-

worthy modification: The tendency to avoid expressing opinions when we are unaware of the

opinions of others is not an online phenomenon. It is equally observable in offline environments

(Ibid.). We are more willing to debate controversial issues with people we feel at least partially

certain to share our views, making our close friends and family the ‘safest’ crowd to debate with.

Social media, and in this case FB, presents users with mixed, unknown territory in which your

opinions (if made available) can be encountered by any number of people. It is this wider exposure

beyond our certainty of likeness and at least partial agreement that make us hesitant to engage in

political debates on FB.

As an extension of the above listed point, to me, Hjarvard’s dismissals of firstly FB as

representative of wider tendencies in the population and secondly the concept of echo chambers

become futile. If we are in fact almost equally hesitant to debate outside of our comfort zones

online and offline, then the image might not be so skewed after all. If it indeed is the few that end

up expressing their opinions, while the rest shy away on some level, then it would not appear to be

an issue interpreting on this as it takes place on FB. Because is the problem he describes – our

tendency to avoid debating with people who’s views we do not know, and to only talk to

likeminded – not exactly one of the points and pitfalls of an echo chamber? Is it not this

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unchallenged narrowing of our communicative behaviour that Hess (2014) is concerned by, when

he addresses the rhetorical nature of algorithms as they provide digital rhetorical identification?

What seems to be missing in Hjarvard’s interpretation of the Danish study is the observation that

the underlying assumption present in the algorithm controlling the News Feed supports our

behaviour as it seeks likeness and agreement. Our tendency – online as well as offline, as Hjarvard

notes himself – to seek out, ‘like’, and share information that we already agree with is an integrated

part of the environment that is FB. This point is observed by a recent article from the Danish

newspaper Berlingske Tidende, bluntly headlined “When FB makes us dumber” (Holm 2016). The

article recounts an Italian study that has traced FB use over five years, from 2010 to 2014, focusing

on the spreading of conspiracy theories versus sober scientific news on the site. The Italian

researchers note how users pick out information that corresponds with a certain worldview, thus

creating, over time, homogenous and polarized clusters of users around them (Ibid.). Users were

unfazed by whether or not the information had much substance or backing to it, they cherry-picked

to suit their views. The study supports the metaphor of an echo chamber to explain how the effect of

the user behaviour results not only in polarization, but also in a stronger confirmation bias with the

users as they become increasingly convinced of their own worldview (Holm 2016). So while FB

cannot be taken to be neutral grounds on which people meet to debate, it does present us as

academics with what I consider to be interesting expressions of what I, on the basis of the issues

discussed so far, interpret to be a somewhat substantial part of the human condition. If data we can

collect from FB mirrors this, then it appears to me that it merely presents us with a possibility of

assessing the effects of people’s echo chambers – as in the FB case, where at least three general

positions are confronted with each other in the comment thread following Kramer’s post.

The reason why this short introductory discussion matters reaches back to Hjarvard’s assertion that

we should be cautious in taking statements on FB to bear any significance towards public opinion,

because of the many things that are supposedly not being addressed by users from fear of

confrontation with non-likeminded. This seems to somewhat ward off considering FB as a platform

suitable for analysis of democratic processes or utterances. While Hjarvard’s observation regarding

our reluctance to debate controversial issues on FB is echoed by the overall observation that we

both like and are encouraged algorithmically to seek out likeness on the platform, I believe that we

miss out on important insights into the formation of opinions and publics if dismiss FB as a

potential platform for the formation of both. As an extension of the work I have done in this thesis, I

believe that we can assess statements made on FB to bear significance towards wider tendencies

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such as public opinion as long as we recognize the intrinsic limitations (the settings of the

algorithm) of the medium as they reflect our apparently human tendencies to prefer likeness to

unlikeness. FB is for the many, of course, a social platform first and a potential political debate

forum second, but what the analysis of the FB case in part was meant to show was that the different

echo chambers can be confronted with each other to reveal the knowledge gaps that set them apart.

Moving towards my final discussion of the consequences algorithms have towards the average FB

user’s enactment of rhetorical citizenship, I first have to address the underlying power structure that

enables all of this in the first place.

5.2 Privately held, publicly trusted Earlier on, I defined algorithms rhetorically given their ability to provide Burkean identification,

limit rhetorical agency, and act persuasively. I employed the writings of Aaron Hess in this

definition, particularly his later work, and in it he noted a potential consequence of the rhetorical

nature of algorithms: “As unconscious devices, [algorithms] positions [sic] users in polarizing

groupings of knowledge (...) these groupings foster inbreeding of argumentation without the users’

knowledge” (Hess 2014, p. 16). As stated earlier, this can result in an overall diminished ability to

empathize within publics and across political persuasions, and Hess asserts that this tendency

extends to the offline world as well. Aforementioned David Beer echoes this observation in his

statement that information technologies do not just mediate our lives, they comprise and constitute

them, and Fenwick McKelvey goes further in his specifications of the possible effects of

algorithms: “Algorithmic control has significant social consequences, not the least of which is the

creating of associations that resemble publics” (Beer 2009, p. 987; McKelvey 2014, p. 597-598). So

algorithms have the potential to create associations that resemble publics, and, at the same time, to

influence us greatly, given the various rhetorical functions listed previously. Earlier on, I cited the

concerns of Lawrence Hinman as they pertained to the limiting effects of search engines on the

circulation of knowledge (2008). I believe this concern to be relevant here, as it encompassed the

‘privately held/publicly trusted’ dilemma, which is also present in the case of FB: “Such control of

knowledge is, in a very fundamental sense, a public trust, yet it remains firmly ensconced in private

hands and behind a veil of corporate secrecy” (Hinman 2008, p. 75). FB is first and foremost a

business, which makes it primarily responsible towards its shareholders, and only secondly it’s

other stakeholders (which includes the users). We end up with a situation where we, the users, place

our trust through repeated usage and the relinquishment of personal data in a platform that is

designed to make us want to do so from a business perspective. Now there is nothing wrong with

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doing business the way FB does, formally. But practically, FB has reached a size and scope that

make them highly influential, beyond the site itself. The important point is that our interaction with

a site such as FB is not isolated to that environment, and our behaviour and ways of interacting with

each other on a societal level is affected by it. As mentioned previously, when we become less

sensitive to “a variety of practices of invention (...), argumentation practices are drastically affected

in traditionally understood offline spaces as well” (Hess 2014, p. 17). As the analysis showed, the

results of increasing polarization might look something like knowledge gaps, which only become

detectable when confrontation between different publics is forced forward by an event that gathers

them on some level, such as the FB case of 2014. These knowledge gaps are not just an academic

musing, or vague and somewhat pointless variations of understanding. As the analysis showed,

knowledge gaps that concern modern digital technology can be of significant size and have severe

and very real consequences. For the providers in this case, FB, the ordeal meant a palpable backlash

from users around the world, causing particularly the researchers responsible a great deal of

personal stress. As Jeff Hancock later described the time following the publication: “...it was very

difficult. I will admit. My family paid a price for it. I paid a price,” (Hancock 2014). For the users

of FB, the realization of the simultaneous extent of their own unawareness and the omnipresence

and impact of algorithms caused equal amounts of desperate, frustrated questioning and anxiety. It

was as if a majority of people suddenly realized what Hinman suggested back in 2008: “These

tangled lines of responsibility,” (i.e. the privately held/publicly trusted situation), “suggest that

public mistrust may be the more appropriate attitude” (2008, p. 75). Of course the question of a

media type being privately held/publicly trusted is not a new one. Some of the reactions from

academics and professionals to the outcry following the FB case sound very similar to that of

Professor at MIT’s Sloan School of Management, Sinan Aral, who is quoted in the previously

analyzed article by Will Knight: ““I was very surprised to see that people were upset about [the

emotional component of the FB study]” he said, pointing out that many television ads and

newspaper headlines are arguably just as emotionally manipulative,” (Knight 2014). There is,

however, a crucial difference between the media types Aral refers to. As Rafi Schwartz notes in his

article “The Polarizing Political Power of News Feed Customization”, algorithmic media presents

users with a new situation:

“What once was a question of consciously selecting a preferred information source from among several has morphed into a world where people are bombarded with a near-endless stream of news options (...) but thanks to the increasingly customizable nature of how we experience news online (...) it’s one which is now bolstered by the systemic structure of our newsfeeds themselves—a hybrid

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of deliberate self-selection and passive, algorithmically driven reinforcement. We don’t just choose our news anymore; it, in turn, is also chosen—tailored, even—for us.” (Schwartz 2015).

In other words, there is a discrepancy between the freedom we are led to feel online, choosing from

seemingly endless lists of possibilities, and the actual situation we face. David Beer labels it “a

rhetoric of democratization”, as the Internet and especially Web 2.0 is introduced to us as a

democratic media type, something that was noted over a decade ago by researchers at London

School of Economics and Princeton, Lucas Introna and Helen Nissenbaum: “Enthusiasts of the

“new medium” have heralded it as a democratizing force that (...) will empower the traditionally

disempowered, giving them access both to typically unreachable nodes of power and to previously

inaccessible troves of information.” (Beer 2009, p. 986; Introna & Nissenbaum 2000, p. 169). Since

Introna and Nissenbaum’s observations, many objections have been made to the portrayal of the

Internet as the great liberator. But what we are seeing now is a different situation, where

algorithmic control is greater than ever – and that begs us to ask the question again: How real is the

representation? Beer continues, “we have so far had little opportunity to explore how new forms of

power play out in this context of apparent ‘empowerment’ and ‘democratization’” (Ibid.). The

connection between algorithms and the FB case as I have analyzed it in this thesis just might be one

of the discourses Beer is looking for. Either way, the actual systemic, algorithmic control that is

being executed out of reach (literally and perceptually) of the average user appear detrimental to

ideals of ‘empowerment’ and ‘democratization’. Building on top of this observation, we can begin

to discuss the impact of algorithms on the enactment of rhetorical citizenship for the average FB

user.

5.3 Rhetorical citizenship in algorithmic environments Rhetoricians Christian Kock and Lisa Villadsen provide a definition of rhetorical citizenship, “as a

discursive phenomenon in the sense that important civic functions take place in deliberation among

citizens and that discourse is not prefactory to real action but in many ways constitutive of civic

engagement” (2012, p. 1). To be a citizen, in this view, is to participate and debate – there is no

citizenship without it being rhetorical (Kock & Villadsen 2012, p. 1-2). I look to scholar Maria

Bakardjieva (2012) for a broadening and deepening of that definition. Bakardjieva insists that

citizenship, overall, is to be considered a process, and one that can and most often do origin in what

we might call the private sphere: The home, the familiar surroundings, the habits you have, and the

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people you surround yourself with. This view stands in contrast to a more classical Aristotelian

interpretation of citizenship, which primarily defines it as civic engagement in a public space32.

From Bakardjieva’s interpretation of citizenship, rhetorical citizenship can be understood on several

levels in society, and not just from the privileged positions of those who have the means and the

ability to express themselves in traditionally understood public spaces. The concept of mundane

citizenship is introduced to cover the process wherein citizenship unfolds – a process Bakardjieva

particularly observes in the average citizen’s adaptation of the Internet (2012, p. 5). Citizenship,

then, is defined as an aspect of our individual identities, which we construct through a variety of

actions that position us in a certain way towards the surrounding society (Ibid.). These positions

gain a political edge when we identify with others, with collective groupings, on what Bakardjieva

labels a “friend-enemy axis”. This is where the definition gets interesting. Bakardjieva’s mundane

citizenship covers the wants, needs, and concerns of the individual, but also the collective

identification process, where mundane citizenship moves from a private to an interpersonal, group,

and finally public discourse (Ibid.). This is the same identification process that algorithms now

stimulate, qua Hess’ digital rhetorical identification (2014). The different levels of political

engagement, as they belong to each group, are labelled: 1) politics proper, the institutionalized and

officially recognized political system, 2) subpolitics, where actors from outside of the political

system appears on “the stage of social design”, and finally 3) subactivism, which denote private and

individual decisions that have a political or ethical frame of reference (2012, p. 6). Bakardjieva

considers subactivism to be a hidden dimension of citizenship, and one that forms the basis for our

further engagement in subpolitics and politics proper (2012, p. 7).

The point of it all is that if our engagement on sites such as FB continues to increase in frequency,

as it has up until now, and we simultaneously are unaware of the algorithms in place that shape our

experiences, then the level of subactivism is potentially tainted. In a sense, Bakardjieva’s process of

citizenship explains the process of political polarization when it comes to the influence of

algorithms in our society today. Rhetorical citizenship for the average user of sites such as FB is

limited as a result of the increasing algorithmic control, because the grounds on which the user

stands are pre-selected and narrowed in advance. When we lose the ability to choose for ourselves,

as we increasingly do, and we at the same time are unaware that this is happening, we end up with a

situation that is the opposite of empowerment and democracy. If rhetorical citizenship is a process

32 For an example of this view, see the chapter “Citizenship as Rhetorical Practice” in Kock and Villadsen (2012).

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through which we become able to participate in society on a higher, more institutional level, then

we are being set up to do so poorly. While a counterargument might go, “People are responsible for

their own stock of knowledge, why is all this even a concern,” the FB case showed us on a small

scale how impactful lack of knowledge can be – in a troubling way. It is, as a result, a shared

responsibility to provide more transparency in an area that apparently lacks it. This assertion,

however, seems to beg the question: Without complete, specific knowledge of the technological

advances that make new media available to us, can we ever interact ‘properly’ and knowingly with

that media? I believe it is possible to vastly increase the level of transparency on algorithmic control

on sites such as FB without the need for all of us to become tech-geniuses or experts. As Eslami et

al showed in their basic design of a FB application, FeedVis, the vast majority of users made

familiar with the algorithmic function of the News Feed through FeedVis returned to normal (and

more informed) use of FB after the study, with the same levels of satisfaction with the site (Eslami

et al 2015). Put bluntly, it seems that people just want to know.

It seems it all comes down to the concept of making an informed choice – which has always been a

process that sparks critical questions. When do we know enough about something? When have we

considered all the possible points of entry to a case in question? To what degree is our subjectivity

guiding our attempts at objectivity, and does it even make sense to try and avoid it? As the distance

between our life online and offline ever decreases, and our searches for knowledge have been

limited to take place on a handful of websites, the process of making informed choices on any level

of citizenship becomes problematic. Rhetorical citizenship, then, is affected for the average user of

sites such as FB. Political polarization is facilitated out of sight and mind as “likeness is good”

shapes the majority of our online existence. This carries over into our actions in the sphere of

politics proper, which is why it matters greatly: We are conditioned daily, in ways not only

unknown but also imperceptible to many people, to identify and act in certain ways. The

interiorization of the media we frequent daily structures our thought processes, and as a new

generation grows up interacting with it from an age where their brains are still developing, the

question of the influence of algorithmic media seems all the more pressing. Returning to Barry

Brummett’s claim for rhetorical criticism’s pedagogical aim, if we are “to teach people how to

experience their rhetorical environments more richly”, this area seems in need of attention

(Brummett 1984, p. 103). From the outset, it was a pedagogical aim of this thesis to ultimately

encourage a more conscious and critical consumption of algorithmic Internet products such as the

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FB News Feed. Moving on from here, as rhetorical scholars – Brummett’s “gatekeepers” – we have

a job at hand. It seems, indeed, to be one of educational ends.

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6.0 Conclusion This thesis set out to answer the research question, “How can we theoretically and practically

approach algorithms from the point of rhetoric, and what contributing points to the wider society

can we observe from such an exploration?” Corresponding with the phrasing of the question, the

work of the thesis was divided into three parts: A theoretical examination of the concept of

algorithms in relation to rhetoric, a practical case-study of an incident where sudden algorithm

awareness was forced about publicly with ensuing strong reactions, and finally a discussion of the

impact of the findings of the two previous parts towards political polarization and rhetorical

citizenship.

Part I established the rhetorical nature of algorithms through a theoretical examination that

determined their ability to affect processes of Burkean identification, rhetorical agency, and

persuasion. The concept of digital rhetorical identification, a modified version of Burkean

identification introduced by rhetorician Aaron Hess, was employed as a substantial part of the

theoretical definition of algorithms as rhetorical constructs. In Part I it was further argued that it

matters to define algorithms rhetorically because of the imperceptibility that surrounds their

workings in the backdrop of online life, which seems to mask the fact that underlying assumptions

about our way of socializing with each other are worked into the algorithms.

As a practical example of the influence of algorithms, and of the public state of awareness of them,

the publication of a FB study from 2014 was employed as a case for analysis in Part II. Through a

pentadic analysis of three overall groups of artefacts, the differences between their constructions of

the particulars surrounding the situation in 2014 were made evident. First, two types of responses

from FB were analysed and found to contain what was labelled semi-apologies: A speech act

approaching an apology, but one that apologizes not for an act but for how the act was

communicated and subsequently received. Second, responses from FB users were analysed to show

how three main stances were formed towards the issue at hand: That of the scholar, the ethicist, and

the outsider. The three stances furthered the argument that algorithm awareness affects not only

usage but also our emotional reactions to Internet products such as the FB News Feed. Finally

entries from a blogger and a journalist were analysed to represent the sentiments of the tech

community towards the ordeal: They were marked more by surprise at the unawareness of their

fellow users than at the FB case itself. Overall, the analysis showed how varying the levels of

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awareness concerning algorithms was with the individual groupings, and how the patterns of

reactions seemed to correspond with the level of awareness present in the individual artefacts.

These differences were interpreted as knowledge gaps, a concept describing the distance between

those aware and unaware of the algorithmic presence on FB, which was introduced for the purposes

of this thesis. The concept of knowledge gaps had further use as a model of explanation for the

relational complications that arose between especially providers and users of algorithmic media

present in the FB case.

Part III discussed the conclusions reached by Part I and Part II, and answered the last part of the

research question, which asked what contributing points one could make to society at large from the

observations made through the theoretical and practical analysis of algorithms in action. The most

pertinent points to be made were related to the problem of political polarization and the potential

demise of rhetorical citizenship as a result of our increasing but uninformed use of algorithmic

media such as FB. Because of the potential impact algorithmic media has on us, especially

regarding the issue of political polarization and the tailoring of our online experiences to suit our

persuasions, this thesis has encouraged further scholarly attention towards the subject area.

In these ways, this thesis has answered the overall research question posed in the problem

formulation. I have argued that it matters to define algorithms rhetorically because of the human

interference their design connotes. To define algorithms as rhetorical constructs, as an extension of

this point, is to accentuate their persuasive measures and to increase transparency on their

characteristics. I have argued that algorithms are inherently rhetorical given their ability to convey

subliminal messages that promote certain actions over others, thus shaping behaviour and thought

processes with users.

If algorithms were more commonly treated as yet another way of influencing others, as

advertisements, commercials and political speeches are today, the FB case from 2014 might not

have been a case at all. It is their imperceptibility that grants algorithms an unfortunate but –

following the findings I have presented in this thesis – undeniable obscurity to the average Internet

user. However profitable Internet products such as the News Feed are, the backlash caused by

incidents such as that of 2014 does not characterize a sustainable provider-user relationship. Such

ordeals cause dents in the public trust in companies like FB that surely are not in their interest. As

such it would seem to serve not only users but also providers of algorithmic media to have the

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general stock of knowledge and algorithm awareness increased – in the words of Brummett, in

order for them to experience their rhetorical worlds more richly.

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7.0 References

ABC News (2014, June 30). Facebook manipulates 700k users' newsfeeds in secret study

prompting backlash. ABC News. Retrieved on September 8 2015 from

http://www.abc.net.au/news/2014-06-30/backlash-over-FACEBOOKs-unethical-secret-

study/5558560

Ananny, M. (2011, April 14). The Curious Connection Between Apps for Gay Men and Sex

Offenders. The Atlantic. Retrieved January 4 2016 from

http://www.theatlantic.com/technology/archive/2011/04/the-curious-connection-between-apps-for-

gay-men-and-sex-offenders/237340/

Bakardjieva, M. (2012). Mundane Citizenship: New Media and Civil Society in Bulgaria.

EUROPE-ASIA STUDIES, 64(8), 1356-1374.

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7.1 Comment references

i Comment by Claire Litton, June 30th 2014, 01:59 ii Comment by John Morrow, June 30th 2014, 02:43 iii Comment by Chris Leeder, June 29th 2014, 23:01 iv Comment by Abhas Gupta, July 4th 2014, 00:37 v Comment by Leah DeRose-Wilson, July 4th 2014, 02:33 vi Comment by Dale Sheldon-Hess, June 29th 2014, 23:11 vii Comment by Cameron White, June 29th 2014, 23:43 viii Comment by Cara Ostomel, June 30th 2014, 05:56 ix For an example, see Marcin Jeske’s comments from July 1st (17:55; 22:59; 23:57) and July 2nd (00:05) 2014 x Comment by Leah DeRose-Wilson, June 30th 2014, 06:06 xi Comment by Susan Liên Whigham, June 30th 2014, 05:41 xii Comment by Brandy Sears, July 1st 2014, 01:13 xiii Comment by Yeliz Karadayl, July 2nd 2014, 21:30 xiv Comment by Susan Liên Whigham, June 30th 2014, 05:41 xv Comment by Fred Zeleny, June 29th 2014 – OBS was edited and the date showing now is June 30th 2014, 14:01 xvi Comment by Michael Higgins, June 29th 2014, 23:52 xvii Ibid. xviii Comment by Nicole Ellison, June 30th 2014, 02:11 xix Comment by Derek Lomas, June 30th 2014, missing time xx Comment by Fred Zeleny, June 30th 2014, 14:01 xxi Comment by Susan Liên Whigham, June 30th 2014, 05:41 xxii Comment by Brandy Sears, July 1st 2014, 01:13 xxiii Comment by Derek Lomas, June 30th 2014, missing time

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8.0 Appendix

8.1 Appendix: Selected Facebook commentary

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