social computing research sept. 6, 2012 uichin lee kaist kse
TRANSCRIPT
Today’s Papers• The intellectual challenge of CSCW:
The gap between social requirements and technical feasibility. Mark Ackerman, Human-Computer Interaction, 15, 179-203, 2000
• The trouble with social computing systems research, Michael S. Bernstein, Mark S. Ackerman, Ed H. Chi, Robert C. Miller, ACM CHI EA, 2011
• The (Anti)Social Net, Elizabeth Churchill, Interactions, 2010
The (Anti)Social Net
• Social network research in early days (~1930s-1950s)– Primarily concerned with people and social
management of relationships and connections– How methods could be triangulated with other
data sources to foster an understanding of how people interact (social behavior)
The (Anti)Social Net, Elizabeth Churchill, Interactions, 2010
The (Anti)Social Net
• Our hats as designers, developers, and business entrepreneurs of social technologies matter (forcing us to forget what social means)– Primary (sensory) vs. secondary experience (rational)
• Developers: excited with hard technical challenges (and overwhelmed with computational power—often leading to overkill)
• Entrepreneurs and media strategists: goggle-eyed for the potential audience reach and the bucks that can be made
• Designers: generally better, but their prevailing logic was often like “let’s go ahead”
The (Anti)Social Net• In recent incidents, social-technical gap was obvious
– Unintended reveal of personal information (e.g., Google Buzz) – Everything is public? (e.g., Facebook’s privacy setting)
• Can we prevent these?– Deeper understanding of what the technology is and how it
fits into people’s everyday lives– Concomitant shift in the way where design decisions are
elaborated and business decisions are made– Evaluation must be well designed; instead of simply doing
“eating your own dogfood”-type of biased “bucket tests” (=user studies)
The (Anti)Social Net• “Social networking sites have focused on networks and individuals.
When it comes to interacting and having relationships, people don’t think in terms of the sum of total connections, and inter-connections they have,
but they think of the individuals they know and the groups they belong to.
People and groups are different from nodes and networks”
“Groupware and Social Dynamics” by Jonathan Grudin (CACM 1994)
The (Anti)Social Net
• Challenges for social network developers– Understand that your intuitions are likely wrong– Broaden your ideas about evaluation– Understand your constituencies – Manage change; don’t’ thrust it on people– Communicate with people who use your site, and
understand what they want to communicate to others and to you
– Develop a clear ethical stance
The intellectual challenge of CSCW: The gap between social requirements
and technical feasibility
Mark Ackerman, Human-Computer Interaction, 15, 179-203, 2000
Social-Technical Gap• Social activities are often very flexible, nuanced, contextualized • We don’t know how to build systems that fully support such social
activities– Technical systems are often rigid and brittle
• Social-technical gap: the divide between what we know we must support socially vs. what we can support technically
• Example: computer-mediated communications still lack much computational support for sharing information, roles, and other social policies
• Exploring, understanding, and hopefully ameliorating this socio-technical gap has been the central challenge in HCI
• Many people worked, yet this gap still exists• We’ll look at Computer Supported Collaborative Works (CSCW) literature to
better understand this socio-technical gapThe intellectual challenge of CSCW: The gap between social requirements and technical
feasibility. Mark Ackerman, Human-Computer Interaction, 15, 179-203, 2000
Well-Known Findings in CSCW
• Social activity is fluid and nuanced– Technically difficult to construct properly and
often awkward to use• Example: access control system– What to release when? – Difficult due to lack of shared histories and
meanings (context)• Exceptions are normal in work processes
CSCW: Computer Supported Collaborative Works
Well-Known Findings in CSCW
• Members in social communities often have differing (and multiple) goals– May be hidden/conflicting goals
• Conflict may be as important as cooperation in obtaining issue resolution
• Finding ways of managing the problems and trade-offs resulting from conflict and coordination
Well-Known Findings in CSCW
• People prefer to know who else is present in a shared space and they use this awareness to guide their work– Control room examples; air traffic controllers
monitor others to anticipate their future workflow– Adding awareness (i.e., knowing who’s present)
and peripheral awareness (i.e., low-level monitoring of others’ activity) to shared communications systems
Well-Known Findings in CSCW
• Visibility of communication exchanges and of information enables learning and greater efficiencies– Situated learning, learning in a community of
practice (e.g., copilots learn from observing pilots work)
– Side effects: criticism, management, formality, lack of sharing, incentives
Well-Known Findings in CSCW
• The norms of using a CSCW system are often actively negotiated among users
• A critical mass problem is important (i.e., # of active users must be maintained; otherwise, “melt-down” will happen)
• People adapt to systems (adaptation); they adapt systems to their needs (coevolution)
• Incentives are critical (e.g., knowledge sharing)
Social-technical Gap in P3P (Platform for Privacy Preferences)
• Privacy control dimension: recipient vs. data itself
• Handling an infinite information space? Can we design such an interface?
• What about underlying social requirements?
• Social-technical gap– Not sufficient nuance (vs. fine-grained distinctions)– Not socially flexible (vs. graceful switching social contexts)– Not sufficiently ambiguous (vs. discrete states)
Technical Research
• Existing studies emphasized a dichotomy:– Designers/programmers vs. social analysts
(nuance/flexibility)• Technical research on bridging the gap– Answer Garden:
• Initial roles: info seeker and provider?• Answer Garden 2: providing ranges of expertise (nuance) + both
seeker/provider (flexibility)
– Concurrency control:• More sophisticated in interactive environments covering s/w, data,
interface • Social context matters with conflicting actions
Technical Research
• We should be aware of the following:– It’s not likely this gap can be solved shortly (though
constantly improving; often, AI-complete problems)– Gap is not historical artifacts; we have been co-
evolving with technology (e.g., neo-taylorist version vs. co-evolutionary version)• Gap is still important; e.g., "round off the edges” of
coevolution
• Socio-technical gap is real important and likely to remain….
What to Do with Social-Technical Gap?
• Is it a black holes or an important aspect?• Research vitality comes from its understanding
of the fundamental nature of the gap• Should we continue to state and restate the
gap?• Research communities should strive to
ameliorate the effects of the gap; and to further understand the gap
Moving Forwards
• CSCW (and more broadly social computing):– Should attempt to construct suitable systems for
groups, organizations, and other collectivities– As a social science attempting to understand the
basis for that construction in the social world (or everyday experience)
• Yet, consider the gap between what we would prefer to construct and what we can construct – Some level of approximation is required
Moving Forwards:Any directions of first-order approximation?
• Partially address the social requirements – Satisfying specific tasks/settings is OK
• Add functions that help people to make social adjustments – e.g., enabling CMC components like chatting
• Incorporate new computational mechanisms:– to substitute adequately for social mechanisms; or to provide for new
social issues – e.g., distorted video/audio images to give social presence
• Create technical architectures that do not invoke social-technical gap as they provide supportive or augmentative facilities like advice to users – e.g., collaborative filtering, recommender systems, critic systems that
make suggestions to users about design choices
Guiding Questions for Researchers
• When can a computational system successfully ignore the need for nuance and context?
• When can a computational system augment human activity with computer technologies suitably to make up for the loss in nuance and context, as argued in the approximation section above?
• Can these benefits be systematized so that we know when we are adding benefit rather than creating loss?
• What types of future research will solve some of the gaps between technical capabilities and what people expect in their full range of social and collaborative activities?
The trouble with social computing systems research
Michael S. Bernstein, Mark S. Ackerman, Ed H. Chi, Robert C. Miller,
ACM CHI EA, 2011
Social Computing Systems Research
• Research whose main contribution is the presentation of a new socio-technical artifact, algorithm, design, or platform
• Envisioning new ways of interacting with social systems; spreading ideas to other researchers and the world at large
• Traditional CSCW/CHI research had full of systems papers (e.g., distributed teams and collaborations)
• Due to a massive growth in platforms, APIs, and interest in social computing, we see lots of new interesting research systems
Social Computing Systems Research
• Reality: 4-1 ratio (understanding users vs. systems, tools, architectures, infra) in CHI 2011
• Challenges– Social computing systems are caught between social
science and computer science, with each discipline de-valuing work at the intersection
– Social computing systems face a unique set of challenges in evaluation: expectations of exponential growth and criticisms of snowball sampling
– How can academic social computing research compete or cooperate with industry?
Social Computing Systems Research
• Caught-in-the-middle in conflicts between builders (computer science) vs. studiers (social science)
• Studiers: strength in numbers– Become a majority in the CHI community– Limited field studies of social computing systems: they worry too much about internal
validity (often requiring large scale studies like A/B tests, long-term evaluation)• Builders: keep it simple, stupid – or not?
– Expecting a contribution with technical novelty: this often translates into elegant complexity (possibly very simple, but interesting ideas); flashy tasks (e.g., end user programming, novel interaction tech)
– But social computing systems contributions are not always in a position to display elegant complexity• Microblogging: very simple, but has social changes• User interfaces (way ahead of adoptions): may not attract much use on social networks• New commenter interfaces: hard to convincing existing users to test them
Social Computing Systems Research
• Caught-in-the-middle:– Making a system technically interesting: but a crowd
will rarely use it because it’s too complex– Simplifying it to produce socially interesting
outcomes– Builders will dismiss papers as less novel; studies
may balk at an uncontrolled field study– Cf) Twitter would not have been accepted as a CHI
paper – no complex design or technical challenges, a peculiar subpopulation-based user study
Judging Novelty• Social contributions change how people interact (enabling new
social affordances—foreign to Builders)– New forms of social interactions: e.g., shared organizational memory– Designs that impact social interactions: e.g., rapidly increasing online
participation– Socially translucent systems: interactive systems that allow users to rely
on social intuitions• Technical contributions: novel designs, algorithms, and infra
(supporting new social affordances—foreign to Studiers)– Highly original designs, apps, and visualizations designed to collect and
manage social data (or powered by social data)– New algorithms that coordinate crowd work or derive signal from social
data (e.g., collaborative filtering)– Platforms and infrastructures for developing social computing apps
Evaluation
• Living lab studies of social computing systems– ?? Expecting exponential growth
• # participants: median of 16 participants (CHI2006)• Usefulness/usability: how to measure usefulness? (e.g.,
voluntary usage vs. fee-based user studies?)• Spread vs. steady-state phases; not required to address
both; also, be careful about your claims about contributions
– ?? Get out of the snow? No snowball sampling• Sometimes it is inevitable in social systems• Random sampling could be impossible • Snowball sample is another form of convenience sampling
Summary
• Social-technical gap is real important and likely to remain; research communities should strive to ameliorate the effects of the gap; and to further understand the gap
• Take off our hats as designers, developers, and entrepreneurs of social tech; focus what social means as primary experience (sensory) instead of secondary experience (rational)
• Unique position of social computing systems research: caught-in-the-middle (builders and studiers), challenges of evaluation (small biased sampling)– How to judge novelty? How to evaluate systems well?
Next Week• Week 2/3: focus on social Q&A
– Recall following week schedule• W4/5/6: Online Community Systems Design• W7/9: Social Media, Social Network Analytics• W10: Ubiquitous Crowdsourcing• W11/12: Human Computation: Basics + Tools + Games• W13: Crowdsensing• W14: Social Tagging and Collaborative Filtering
• Reading assignments (pick one paper)– Knowledge sharing and yahoo answers: everyone knows something,
Lada A. Adamic, Jun Zhang, Eytan Bakshy, Mark S. Ackerman, WWW 2008
– Understanding Mobile Q&A Usage: An Exploratory Study, Uichin Lee, Hyanghong Kang, Eunhee Yi, Mun Y. Yi, Jussi Kantola, CHI 2012