check yourself before you wreck yourself: twitter, buyer's remorse, and self-affirmation theory

Check Yourself Before You Wreck Yourself

Twitter, Buyer’s Remorse, and Self-affirmation Theory

Dave Girtman

COM6400-01

12 July 2013

Dave Girtman 12 July 2013

Abstract

With today’s society moving toward an always-on digital lifestyle, new forms of

communication and interaction offer new opportunities to extend past research. Claude M.

Steele’s self-affirmation theory, developed in the 1980s and 90s, follows the reaction of a

person when he or she is presented with an act or information that causes dissonance and

threatens his self-integrity. I set out to see if this theory holds true on Twitter in the context of

buyer’s remorse. On the day a major upgrade was announced for Apple’s iOS smartphone

platform, I sampled the reactions from Twitter users across all smartphone operating systems.

Though the data shows a pronounced difference in opinions when comparing iOS users to non-

iOS users, there were many uncontrolled variables I could not account for. Thus, I am unable

to draw definitive conclusions about the impact of self-affirmation theory when viewed through

the lens of tweets immediately following a potentially dissonant event. The results of this

study, though preliminary, identify several new opportunities for meaningful research on the

topic. Twitter is set to grow in user base and influence over the next several years, making

additional study paramount to understand how traditional theory will adapt in response to this

new medium.

Introduction

The purchase of a smartphone involves significant costs—be it the up-front cost of the

phone itself, the monthly service cost (often under a contract lasting two years and totaling

several thousand dollars), or the potential cost of a device not being an adequate fit for the

purchaser’s unique preferences and use-cases. This significant investment may cause users to

wonder if they have made the wrong purchasing decision (commonly referred to as buyer’s

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remorse), and it may affect their reactions to news about mobile platforms, be it one they

invested in or another.

The smartphone platform wars now have four major competitors vying for users: iOS,

which is developed by Apple, Google’s Android, Microsoft’s Windows Phone, and

BlackBerry, developed by BlackBerry (née Research in Motion). Mobile devices are

responsible for a sharply-increasing share of Internet traffic (Accenture, 2012, p. 7), and these

major, international corporations are fighting for as much marketshare as possible in this new,

growing technology space.

One of the major ways these companies work to maintain and grow their user base is by

releasing large, yearly updates to their mobile operating systems (OSes), adding features, fixing

bugs, and improving responsiveness and speed. These milestone OS updates are generally

announced with extravagant, multi-hour keynote addresses in which the companies fully unveil

the cornerstone features and improvements upon which they have been working.

These keynotes are major media events, with dozens or hundreds of outlets in

attendance to report back on the day’s news. In the past few years the concept of a ‘live-blog’

has taken hold, wherein technology sites in attendance will photograph and type up news as it

happens, all in the span of less than a minute. These updates are instantly pushed to the outlets’

websites and then also to social media such as Twitter and Facebook.

Twitter is a service for posting and sharing short, 140-character messages known as

‘tweets’ for friends (or anyone else) to see. Users can subscribe to (or ‘follow’) other users,

whose tweets are fed into the ‘timeline,’ which serves as the primary view for reading. Tweets

can include links to websites, stories, or photos, and users can ‘retweet’ posts they find

interesting or informative, adding them to their timeline for followers to see.

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Since its launch in 2006, Twitter has become a well-regarded destination for up-to-the

minute news and reactions to breaking news stories. In April 2013, when two domestic

terrorists detonated bombs near the finish of the Boston Marathon, Twitter user

@Boston_to_a_T was one of the first to post the news with a simple tweet stating “Explosion

at coply [sic]” with a picture attached of a fireball. Over the following days, the service proved

invaluable not only to the public seeking information about the attack and subsequent

investigation, but also to the authorities endeavoring to provide fast, accurate, widely-

disseminable information (Gilgoff & Lee, 2013).

Every year at the beginning of June, Apple hosts the Worldwide Developer’s

Conference (WWDC) in San Francisco, California. At each WWDC since 2007, Apple has

used the opening keynote address to unveil a new version of the iOS smartphone platform,

which powers their iPhone, iPad, and iPod touch product lines.

On June 10th, 2013, Apple unveiled the newest version of iOS, dubbed iOS 7. The new

version came with a lengthy list of feature upgrades, most noticeable being a total redesign of

the operating system’s look and feel. The new software was not actually released that day;

Apple generally reveals iOS updates five to six months before they are released to the public,

so any reactions that day were based on sight alone. Opinions are generally polarized when a

widely-used piece of software is given a major makeover (see: any time Facebook has launched

a redesign in the past five years), so the unveiling of iOS 7 provided an opportunity to gauge

real-time, off-the-cuff reactions of all different types of users, be they iPhone owners or

otherwise. With Twitter as a source of fast, honest reactions from users across the world, I set

out to study whether Claude M. Steele’s self-affirmation theory is evident in the tweets

immediately following the announcement of an iOS update.

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Literature Review

Various researchers have tackled the idea of the self and the methods or justifications

for its preservation in the face of dissonant acts and information, primarily spearheaded by

Claude M. Steele’s 1988 paper on sustaining self-integrity. The prior research has focused on

the self-system and the maintenance thereof, on the affect of dissonance, and the role of

confirmation bias in preservation of the self.

The Self-system

Steele argued for the existence of a self-system that interprets incoming information so

as to “affirm the goodness, strength, and stability of the self” (1988, p. 266). This self-system

rises from a ‘totalitarian ego’ that works to preserve the structure it operates within. When

presented with dissonant information, this totalitarian ego molds the incoming dissonance so as

to preserve the self’s status quo and eliminate conflict within the mind (Greenwald, 1980, p.

614).

The purpose of the self-system, according to Steele, is to mediate the feelings of self

with the external information coming from the world around us, thus preserving the notion of

the self as good, defensible, and morally pure. In other words, the self-system serves to

“explain ourselves to ourselves” (1988, p. 266). This system reinforces our attitudes relating to

social issues—attitudes that are built upon our own untested assumptions, preconceptions, and

memories (Lord, Ross, & Lepper, 1979, p. 2098).

There is one major area that previous research has left for future study, that of culture’s

role in the self-system. The authors have warned that a society’s effect on the self-system and

its role in self-affirmation has not yet been tested, and could vary widely based on the type of

culture. For example, Sherman & Cohen posit that the integrity of the self may be less

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important when considered in the context of a more collectivist society, one that values the

whole over the individual (2002, p. 122). The present question of Twitter use as a means of

self-affirmation focuses on English-speaking cultures (primarily Americans due to differences

in time zones during the collection of data), so this notion of collectivism may not apply due to

the United States being more individualistic in nature. Further research would benefit from

studying individualist and collectivist cultures separately to monitor for any differences in self-

affirmation.

Maintenance of the self

One point stressed by all of the authors referenced is that the goal of this self-system is

to keep steady the overall perception of self-integrity. The system may choose to specifically

dismiss threats to the self as they are presented, or simply affirm some other portion of the self

to counterbalance the dissonance (Steele, Spencer, & Lynch, 1993, p. 885). Claude M. Steele

proposed that threats to the self “arouse a motive to reaffirm the self, to reestablish a perception

of global self-integrity” (1988, p. 290), and the methods of adaptation “will be determined by

availability” (p. 293). When given time to reflect on the dissonant information, a person may

choose to affirm some other positive aspect of the self to maintain integrity equilibrium, but

when time is limited s/he may instead choose to dismiss the threatening information. Given the

immediacy of Twitter as previously discussed, it would follow that given the two options I

should expect to see dismissal of threatening information rather than an unrelated self-

affirmation.

This choice of options when faced with dissonant information exemplifies the flexibility

of the self. Steele remarked that people may endeavor to eliminate or diminish the threat

directly or lessen the belief that the dissonance is a threat to self-integrity (Steele, 1988, p. 289).

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Research presented in his article was concerned with “how people cope with the implications of

threat to their self-regard rather than on how they cope with the threat itself” (p. 263). If the

user of another mobile platform felt the new features in iOS 7 constituted a threat to his self-

worth, I would anticipate statements deriding the value or utility of specific new features.

The role of dissonance

A primary distinction made by Steele is the difference in a threat’s effect on self-

welfare versus a threat’s effect on self-regard (1988, p. 263). In my study, news about the new

features of iOS 7 would not have any effect on a Windows Phone user’s welfare, for example,

but the perception that iOS may objectively be a better smartphone platform could affect self-

regard, leading to statements aimed at discrediting the dissonant information.

One of the forerunners on the role of cognitive dissonance, Elliot Aronson, posited that

dissonance-inducing actions would cause a stronger self-preservation response among those

with high self-esteem (in comparison to those with low esteem) because the dissonance would

be more out of place among those with a positive self-concept (1969, pp. 26-27). His

prediction surfaces an important question for future research, that of the preexisting condition

of a person’s self-esteem and its affect on protecting the self. This being an uncontrolled study

of Twitter users, a person’s preexisting level of self-esteem cannot be determined, making its

role in self-affirmation ripe for further study.

Steele discussed a study of the effect of name-calling on self-preservation in which a

group of women were called by a researcher posing as a pollster. A subset of the women were

assigned to the ‘name-calling’ group, wherein the pollster told the participants it was common

knowledge they were uncooperative when it came to community projects (1988, p. 264). The

net effect of the name-calling was to “arous[e] a general ego-protective system” (p. 266) which

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led that group to be more willing to volunteer in future community events. In Steele’s words,

“What disturbed the women in the name-calling experiment about being called uncooperative

with community projects was apparently not the inconsistency established by the name, but the

threat to their sense of being good people” (p. 269). The threat was not in the inconsistency but

rather the “implication that one is foolish or unable to control important behavior” (p. 262). In

the face of information that another smartphone platform may be better than the one chosen by

a user, the onset of buyer’s remorse could trigger that very implication.

Self defense

Upon being presented with a threat to the self, the self-system posited by Steele will

activate and apply pressure for adaptation (be it cognitive or behavioral) until the threat is

neutralized and the self is restored (1988, p. 261). In response to this pressure for adaptation,

Steele, Spencer, & Lynch claimed, “people will affirm their self-adequacy through whatever

means is most available or salient” (1993, p. 889). If a person is discovering dissonant

information via Twitter, it stands to reason that Twitter is the most available means for

affirming self-adequacy. Even if a user does not respond by affirming an unrelated aspect of

the self, a negative response is a sufficient means of adaptation until the self is made whole

again. In that case, I might see substantially more negative reactions to iOS 7 from non-iOS

users.

The immediate efforts to self-affirm are often focused on the newfound threat, either by

diminishing its importance or rationalizing its effect on the self (Steele, Spencer, & Lynch,

1993, p. 889). The authors later claimed time elapsed may be a factor in how a person

reconciles dissonant information (p. 892). By pulling a scrape of Twitter as the Apple keynote

was in progress, it was my hope that I could avoid time as a factor in the role of affirmation.

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But my effort to obtain a larger sample of data ended up reintroducing elapsed time as a

variable in the data. The scrape continued for several hours after the Apple keynote’s

conclusion, leaving the possibility that a user would post a reaction to the new features of iOS 7

minutes or hours after learning of it’s unveiling. Because the scrape continued into the evening

of June 10th (and because not all users on Twitter learned of iOS 7 concurrently with its reveal),

the dataset likely contains a mix of immediate and delayed reactions to the news. Further

research may wish to specifically examine time as a variable. Again, if a user has discovered

dissonant information via Twitter, and the first attempts at resolving conflict of the self are

aimed at diminishing the threat, it would stand to reason that the first attempt at reaffirming the

self would take place via Twitter, as it would be the most immediately available avenue for the

user.

Confirmation bias

The concept of the fanboy, a person irrationally devoted to a specific product or idea, is

readily apparent in the technology community when visiting the comments section of tech

articles or perusing forums related to technology topics. This ‘fanboyism’ spreads to Twitter,

with adherents to certain products rabidly defending their preferences. Lord, Ross, & Lepper

wrote that when a new piece of information is relevant to a pre-existing belief, the information

will not be judged impartially, but the reaction would be “biased by the apparent consistency of

that evidence with the perceivers theories and expectations” (1979, p. 2099), leading to an

interpretation that serves to maintain the beliefs already held.

Even when information is neutral and does not lend credence to one position or another,

people are likely to interpret the data as supportive of their personal opinion. Lord, Ross, &

Lepper presented neutral information about the efficacy of the death penalty in reducing crime

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to two groups of participants (either pro- or anti-death penalty), and a majority subjects on each

side interpreted the information as supportive of their own position (1979, p. 2101), and ended

up serving to “increase further the gap between their views” (p. 2105). The expectation for my

research study is that iOS and non-iOS users, when given the same information about iOS 7,

will become more entrenched in their beliefs as a means of self-preservation.

The research by Steele and others so far has focused on offline acts and information as a

means of triggering a self-affirmation response. My goal is to learn if mediated buyer’s remorse

(triggered in the form of news about iOS 7) is enough to merit a self-protective reaction.

Research Experiment

Twitter has a fairly robust Application Programming Interface (API) which allows

independent developers to build and release applications for reading, posting, and otherwise

interacting with tweets on a wide variety of platforms, both desktop and mobile. By parsing

metadata in DiscoverText, it becomes relatively simple to group tweets by the smartphone

platform from which they were posted.

On June 10, 2013, I created a scrape of Twitter data via DiscoverText beginning at 1pm

(the start of the keynote) with the keywords “#WWDC” and “Apple iOS,” updating every 15

minutes until 8pm EDT. I followed along with the Apple keynote live as it happened via

several live-blogs (such as www.TheVerge.com and www.MacWorld.com) and via Twitter

itself. Each time a major new product, redesign, or feature was announced, I added those

keywords to the scrape. Keywords included references to a complete redesign of the user

interface, a new “Control Center” with quick access to commonly used toggles such as

Bluetooth or Wi-Fi, and updates to Apple’s natural-language voice assistant called Siri. By the

end of the keynote, the terms being scraped from Twitter were as follows:

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Terms scraped from Apple WWDC keynote

#WWDCApple iOS

iOS Control CenterSiri

iOS redesigniOS multitasking

iTunes RadioNotification Center

Once the keynote was over and the scrape was complete, I separated the 45,677

collected tweets into buckets based on their device of origin. No pre-existing smartphone

preferences can be determined of users who post from Twitter.com or any desktop apps. To

exclude those non-smartphone tweets (and to account for apps that do not identify their

smartphone platform in the title), I set out to select tweets from the top ten apps for each

platform.

For iOS I browsed the App Store’s “social networking” category by most popular,

selecting the top nine Twitter apps—the tenth ‘app’ included is the tweeting functionality built

into iOS itself. Searching the Google Play store for “Twitter” and pulling the ten most popular

results netted the Android sample. The same procedure was followed for Windows Phone

(except by searching the Windows Phone store). There were only eight Twitter apps to be

found, so all were included. Only two Twitter apps were available for the new BlackBerry 10

platform at the time of the study, and both were included in the scrape. The full list of apps,

along with the total number of tweets collected for each platform:

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Android Blackberry iOS Windows Phone

Buffer

Carbon for Twitter

Echofon for Twitter

Falcon

Hootsuite for Twitter

Plume for Twitter

Seesmic*

Tweetcaster for Twitter

Twitter for Android

Ubersocial for Twitter

Neatly

Twitter for Blackberry

Echofon

HootSuite**

iOS

Tweetbot

Tweetcaster

Tweetlist

Twittelator Neue

Twitter for iPhone/iPad

Twitterrific*

Ubersocial

Mehdoh

Peregrine*

Rowi

Tweet+

Tweeter*

Tweetcaster*

Tweetplus*

Twitter for WP

3,032 613 14,556 174

*App was not represented by any tweets in the scrape of data**HootSuite has apps for several platforms, but each version simply reports its name as “HootSuite.” Because no reasonable determination could be made as to their platform of origin, tweets from this app were excluded.

Once the tweets were separated into buckets, I sampled them into datasets for coding. I

endeavored to code at least 10% of the tweets on each platform (with a minimum of 500 per).

The final numbers came out to 500 for Android and BlackBerry, 1,400 for iOS, and 174 for

Windows Phone. The incredibly large number of iOS tweets may be explained by a few

factors—first, as the news was about iOS, those users had more reason to care because the

update will directly affect their phone usage. Also, many iOS Twitter apps function on both the

iPhone and iPad with a single name, leading to a possible oversampling of data.

The codebook

After a few rounds of discussion and revision, the following codebook was agreed upon

with an inter-coder reliability of .81:

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Positive- These tweets are generally favorable in attitude to iOS 7. They may compare

the new features to those of another smartphone platform, but not in a negative light.

Negative- Generally unfavorable in attitude to iOS 7. They may compare iOS to

another smartphone platform, but in a negative way. Tweets that mention features

Apple “copied” or “stole” go here.

Neutral/Informative- Tweets commenting on iOS 7 without a value judgment either

way. The vast majority of these tweets are from news outlets simply reporting on the

new features (along with user retweets of the same). Humorous or joking tweets about

iOS 7 go here as well. For example, a parody Darth Vader account’s tweet of “Apple

announced Siri will now have a male voice. If it's not mine, Apple is doing it wrong.

#SiriMaleVoice” was coded as neutral.

Unsure- Tweets that mentioned positive and negative aspects of iOS 7 without making

a final judgment, or tweeters that used “I don’t know” when describing their reaction,

were coded here.

Other language- Tweets in languages other than English whose intent cannot be

determined fall under this code.

Unrelated- Tweets that were unrelated to the iOS announcement. These are tweets

posted before the keynote began, or tweets accidentally picked up by the scrape (there

were a decent number of tweets about users wanting apple pie, for example).

Because the study is looking for reactions to potentially dissonant information in non-

iOS users, the iOS category serves as a kind of control group. If there are a large number of

negative tweets from iOS users (or if the negatives are in line percentage-wise with other

smartphone platforms), I might see that self-affirmation theory does not apply in this space.

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Results

Android Blackberry iOS Windows0%

5%

10%

15%

20%

25%

30%

35%

40%

Tweets regarding iOS 7, by platform

PositiveNegativeUnsureNeutralUnrelatedOther lang

For each platform, a plurality of tweets were neutral or informative in nature, simply

spreading the news of and riffing on the day’s announcements and coming in at 32%, 35%,

37%, and 29% respectively. This finding fits with the previously-stated trend of Twitter being

a go-to source for breaking news; the announcement of iOS 7 was big in the world of

technology, and many tweeters were simply posting a link to the Apple website or retweeting a

news outlet’s story about the new features.

Large portions of all tweets sampled (38%, 48%, 45%, and 41% respectively) were

either unrelated to the iOS announcement or posted in a language other than English and were

thus excluded from the analysis. When boiled down solely to tweets with some form of value

judgment, a clearer picture emerges:

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5%

10%

15%

20%

25%

iOS 7 tweets that expressed an opinion

PositiveNegativeUnsure

As I expected, there are a larger number of negative tweets regarding the announcement

of iOS 7 from platforms other than iOS and relatively more positive tweets from iOS users.

Android and Windows Phone users were most likely to express a negative opinion, coming in

at 23% and 22% of tweets respectively. Android users were also much more likely to express a

mixed or unsure opinion of the new OS—a full 17% of tweets were coded as Unsure, compared

to 0%, 2%, and 2% for the other platforms.

Discussion

Buyer’s remorse is probably the most accurate description of the feelings threatening

the self in this type of research. It is, after all, a natural response to seeing a product that is

shiny and new—the idea that one no longer has the best of something because of a poor

purchasing choice may trigger a response to “affirm the goodness, strength, and stability of the

self” (Steele, 1988, p. 266). According to the prior research on the topic, a negative response to

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dissonant information may be a sufficient means of adaptation until the self is made whole

again (p. 267), which the volume of negative tweets from non-iOS users seems to pan out.

The most common complaint from non-iOS users following the Apple keynote was that

Apple ‘stole’ features from other apps and platforms. The most retweeted post among non-iOS

users in the aftermath of the keynote was from tech blog TechCrunch, reading “iOS 7 Steals

Mailbox's Gestures, Sunrise's Layout, BB10's Back Button, WebOS's Multitasking” (Dillet,

2013). (The article posted screenshots of iOS 7, pointing out any and all marked similarities

with the stated apps and OSes.) By spreading this message of gratuitous borrowing from other

platforms, it would seem that non-iOS users are claiming a sort of ownership of the new

features as a way to resolve the possible dissonance of buyer’s remorse. Whether Apple’s

implementation of a feature found in another OS is better is then rendered irrelevant to the self

if a user can convince himself the feature is one to which he already had access.

That TechCrunch tweet was by no means the only negative reaction to the iOS

announcement retweeted by multiple users. The large aggregate number of retweets may

suggest that users do not necessarily have to make their own personal statement to eliminate

dissonance. Surely not every person will consider a retweeted post to be an endorsement of

that tweet’s views or statements, but the large numbers suggest that simply agreeing with a

statement publically could be a way to adapt to dissonant information.

As an aside, the number of retweets from major news sources (of stories both positive

and negative in reaction to the day’s announcements) suggests that the two-step flow of

communication as described by Elihu Katz is alive and well on Twitter today. This new digital

medium seems to preserve the role of opinion leaders in influencing public opinion. By

retweeting news from major outlets, these opinion leaders are disseminating the news to their

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followers who may not be so plugged into the media. Whether or not the retweets lead to a

change in attitudes among those who follow the opinion leaders is not clear and cannot be

determined from this study, but it is an interesting pattern in the data that could use further

study.

The large, immediate number of negative reactions by non-iOS users to the

announcement of iOS does seem to fit with Steele, Spencer, & Lynch’s thought that the system

will dismiss threats to the self as they are presented (1993, p. 885). This immediacy of Twitter

as a medium and the ease of responding as news happens would seem to lend credence to the

notion. The same authors also claimed users will affirm the self “through whatever means is

most available or salient” (p. 889). If a person learns of dissonant news via Twitter which then

triggers the need for a self-affirming response (as may be evident in this study), Twitter would

likely be the most available and salient means of response, leading to statements designed at

restoring self-consonance. With the number of negative reactions to iOS 7 from non-iOS users,

the data collected appears to fit this expectation.

But because the scrape ran for several hours, those negative tweets may not have been

posted immediately after a user learned of the dissonant information. Further research may

want to scrape Twitter for a much shorter length of time following a dissonance-inducing event

to test this immediacy principle. While the sample would likely be much smaller, a very short

window of study would provide new insights into the immediacy of self-affirmation.

With respect to the idea of threats to self-welfare vs. self-regard, the concept of buyer’s

remorse fits soundly in the latter category. Steele discussed a study of cigarette smokers and

their maintenance of self-regard in the face of a mountain of evidence about the dangers of

tobacco. He found that the smokers were generally unable to improve their self-welfare (i.e.,

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improve their health by quitting smoking), but they were able to maintain their high self-regard

through some form of affirmation, be it discrediting evidence against smoking or simply

reaffirming another positive quality of the self (1998, pp. 262-263). Making a poor purchasing

decision about which smartphone platform to invest in may inconvenience a user, but his

welfare will likely never be threatened because of it. Because it is more malleable than self-

welfare, it would seem these issues of self-regard stemming from buyer’s remorse are the easier

of the two to correct.


2%

4%

6%

8%

10%

12%

14%

16%

18%

Tweets unsure about iOS 7

One of the more curious results of the research is the large number of Android users

whose reactions to the iOS 7 announcement fell into the “unsure” category, more than those of

every other platform combined. There are two possible causes for this number. First, the data

may suggest that an announcement such as this is not always immediately a cause of

dissonance, but that it may require some time for users to take in the information and form a

more reasoned judgment. It is also possible that these “unsure” tweets were posted some time

after users learned of the announcement, thereby avoiding a knee-jerk reaction and instead

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offering a more reasoned critique. My thought is that the latter holds truer than the former, but

additional research with a larger sample of data is necessary to draw any kind of sound

conclusion. Why so many Android users in particular were unsure about iOS 7 is a mystery.

There is no concrete evidence to explain the discrepancy, but it may stem from the fact that iOS

and Android are the most visually similar platforms of the four included in this study.

Steele suggested an additional avenue for people to resolve the dissonant information,

by doing something “after a dissonant act that [leaves] the inconsistency intact but affirm[s]

their larger self-worth” (1988, p. 270). This is a much harder concept to test in this study, as I

was looking specifically for users who mentioned iOS and its new features. This assumption

may be tested in the future by observing non-iOS users’ tweets to look for any unrelated, self-

affirming statments. If these self-affirmations are found, it may be a good indicator of this

portion of the theory’s presence in the digital world.

Of course, another plausible explanation of the data is that the update to iOS is simply

not a good fit for a number of users’ needs. A smartphone is one of the few things most people

carry on their person at all times, and as a result the choice of platform is deeply personal and

tied to each individual’s specific requirements. This version of iOS in particular is bound to be

polarizing, as the user interface has been given a completely new design with extra interaction

paradigms, new forms of transparency and spatiality, and a rather bold palette of pastel colors

unseen in previous versions.

It also makes logical sense that a non-iOS user is currently a non-iOS user precisely

because Apple’s platform is not a good fit for his needs. These ideas put a severe damper on

the notion that self-affirmation in the face of buyer’s remorse is the only factor at work here. A

more expansive study comparing users’ pre-existing preferences in smartphone platforms

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(beyond simply their choice of phones) with their post-announcement tweets would likely shed

more light on the topic.

Conclusions

It appears from the data collected that the public is utilizing Twitter primarily to obtain

and spread news or simply joke about current events and topics. This finding serves to

reinforce the thought that during moments of breaking news, users are more concerned with

disseminating information than they are with reacting to it. Positive and negative reactions to

the announcement of iOS 7 were smaller in number compared to neutral, informative tweets.

This may suggest dissonant information is not immediately cause for an affirmational response.

Further research might look at the effect of reactions to iOS 7 in the weeks following its

announcement, and a study of reactions after the update is finally released this fall would make

for an excellent comparison to the data collected here.

But among tweets that expressed an opinion of the day’s announcements, the data

collected may suggest some form of self-affirmation is evident. The comparatively large

number of negative responses from non-iOS users might indicate news of a competing

smartphone platform’s improvements is a source of dissonance leading to buyer’s remorse and

triggering a self-affirmational response, as predicted by Claude M. Steele and others. However

this may only be a result of selection bias—users who purchased an iPhone were already more

likely to enjoy iOS and its updates, just as users who purchased a non-iOS smartphone were

already more likely to prefer another platform. These positive, negative, and neutral reactions

still pale in comparison to the overall number of tweets, so if self-affirmation truly is necessary

in these situations, it is apparently not required by a large portion of the audience.

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This study was only focused on the announcement of one smartphone platform, iOS,

and as such it does not give us a full picture about Twitter users’ attitudes and reactions. A

further study would be wise to pull a similar scrape of data during and after the reveal of a new

version of Android or Windows Phone. Only then could we get a more accurate picture of the

whole—namely, the reactions of iOS users when faced with a competing platform’s update.

There are too many variables in play to form any definitive conclusions about whether

this type of competing product information is a cause of dissonance and self-affirmation. The

unknown length of time between a user learning of the update and posting a reaction to Twitter,

and the issues of pre-existing personal preference for smartphone platforms are not addressed

by this study. These present excellent opportunities for future research on the topic.

Further study should also examine other product categories or topics unrelated to

consumer technology or purchasing behavior. Topics such as racism, economic inequality, or

issues of morals may provide a stronger window into the user’s need for an affirmational

response. Timing is a variable worthy of additional study—does an affirmation have to be

immediate, or can it be some time after a user learns of dissonant information? The question of

collectivist vs. individualistic cultures deserves more research as well. The United States is a

more individualistic society, and a comparison with users in a collectivist culture such as China

may provide further insight.

So while no definitive conclusions can be made from this one study, it does serve as a

launching point for extra, more focused research on the topic of self-affirmation in the world of

Twitter. Going forward, more studies would be wise to take much larger samples of data and

experiment with timeframes, cultures, and pre-existing preferences on a topic. Twitter is still a

growing and evolving medium for communication, and with the kind of expansion it has seen

21


in its first seven years of existence, there is no doubt its influence and reach will continue to

grow for the next several years. With growth comes opportunity, and there is much research

left to be done.

22


Works Cited

Accenture. (2012). Mobile Web Watch 2012. Retrieved July 3, 2013, from Accenture:

http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Mobile-

Web-Watch-Internet-Usage-Survey-2012.pdf

Aronson, E. (1969). The Theory of Cognitive Dissonance. Advances in Experimental Social

Psychology , 1-34.

Dillet, R. (2013, June 10). iOS 7 Steals Mailbox’s Gestures, Sunrise’s Layout, BB10′s Back

Button, WebOS’s Multitasking. Retrieved July 1, 2013, from TechCrunch:

http://techcrunch.com/2013/06/10/ios-7-steals-mailboxs-gestures-sunrises-

layout-bb10s-back-button-weboss-multitasking/

Gilgoff, D., & Lee, J. (2013, April 15). Social Media Shapes Boston Bombings Response.

Retrieved July 3, 2013, from NationalGeographic.com:

http://news.nationalgeographic.com/news/2013/13/130415-boston-marathon-

bombings-terrorism-social-media-twitter-facebook/

Greenwald, A. (1980). The Totalitarian Ego. American Psychologist , 603-618.

Lord, C. G., Ross, L., & Lepper, M. R. (1979). Biased Assimilation and Attitude Polarization:

The Effects of Prior Theories on Subsequently Considered Evidence. Journal of

Personality and Social Psychology , 2098-2109.

Sherman, D. K., & Cohen, G. L. (2002). Accepting Threatening Information: Self-

Affirmation and the Reduction of Defensive Biases. Current Directions in

Psychological Science , 119-123.

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Steele, C. M. (1988). The Psychology of Self-Affirmation: Sustaining the Integrity of the

Self. Advances in Experimental Social Psychology , 261-299.

Steele, C. M., Spencer, S. J., & Lynch, M. (1993). Self-Image and Dissonance: The Role of

Affirmational Resources. Journal of Personality and Social Psychology , 64 (6), 885-

896.

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