This document provides an agenda for a lecture on social computing in human-computer interaction. The lecture covers: 1) Defining social computing and examples of social computing systems. 2) The value of social computing, including enabling new mechanisms of interaction, leveraging collective intelligence, and facilitating human-computer collaboration. 3) Considerations for designing social computing systems, including the need for user-centered and multi-disciplinary approaches. 4) Research areas related to social computing like computer-mediated communication, online communities, and computational social science. The social aspects of research communities are also discussed.

1. Interaction Beyond the Individual:
A Lecture on HCI-Oriented Collaborative and
Social Computing
Hao-Chuan Wang . 王浩全
Department of Computer Science
Institute of Information Systems and Applications
National Tsing Hua University, Taiwan
http://www.cs.nthu.edu.tw/~haochuan

2. NTHU Collaborative and Social Computing (CSC) Lab
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3. Agenda
• What: Social computing in Human-Computer
Interaction (HCI)
• Why: Value of social computing
• How: Design of social computing systems
• How: Research in social computing. CHI & CSCW.
• Reflection
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4. Some References
Thomas Erickson’s Tutorial on Interaction-Design.org
http://www.interaction-
design.org/encyclopedia/social_computing.html
Panos Ipeirotis’ WWW 2011 Tutorial
http://www.slideshare.net/ipeirotis/managing-crowdsourced-
human-computation
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5. What is Social Computing
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6. HCI: Studying the Existing and Possible Relationships between
Computers and People
ACM SIGCHI Curricula 1996 (15 years ago)
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7. Observation from Today
Nothing wrong, but slightly
outdated. What’s
changing today?
- Much emphasis is on the
context of use
- Computers are more
powerful and can look
and work very differently
- Not necessarily “one
human, one computer”
- Computer-mediated
human-human interaction
becomes commonplace
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8. Examples: MSN, QQ
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9. Skype
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10. Twitter, Plurk
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11. Facebook, Google+
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12. Amazon.com
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13. Wikipedia
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14. What’s common among these systems?
1. Technology-mediation
2. ?
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15. What’s common among these systems?
1. Technology Mediation
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16. What’s common among these systems?
1. Technology Mediation
2. Social Interaction
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17. The Invisible Computers
Question: Consider your recent experience of online
communication (email, IM, Skype, Facebook), rank the
salience of the following targets:
(A) Computers
(B) People you talk to
(C) Tasks you do with people
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18. The Invisible Computers
Question: Consider your recent experience of online
communication (email, IM, Skype, Facebook), rank the
salience of the following targets:
(A) Computers
(B) People you talk to
(C) Tasks you do with people
Most likely orderings: B, C, A or C, B, A.
Computers play more of mediating roles, and can be
invisible to users. Social interaction can matter more.
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19. Computing Systems with Significant “Social Layers”
“The social layer” as what distinguishes them from other
computing systems
• Email, MSN, Skype are valuable because they support
remote communication
• Facebook won’t be as rich and attractive if we did not have
many friends using it
• Wikipedia becomes another content-less website if it does
not have all the mechanisms for supporting users’
collaborative editing of content.
An emerging category: Social Computing
Not all technical, not all social, but “socio-technical”
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20. Defining Social Computing
“Social computing refers to systems that support the
gathering, processing and dissemination of information
that is distributed across social collectives.
Furthermore, the information in question is not
independent of people, but rather is significant precisely
because it linked to people, who are in turn associated
with other people.”
– Thomas Erickson, IBM Research
http://www.interaction-design.org/encyclopedia/social_computing.html
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21. Why Social Computing?
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22. Value of Social Computing
Enabling mechanism
• Breaking existing constraints
Efficiency of processing
• Integration of collective efforts
Quality of outcomes
• Social input, synergy
Human-machine collaboration
• Leveraging unique human processing abilities
• Augmenting human processing
Unique value can emerge from coupling people & enabling
interpersonal communication with technologies
http://www.interaction-design.org/encyclopedia/social_computing.html
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23. Enabling Mechanism: Breaking the Constraints
Ex. Computer-mediated communication tools enable remote
communication and distributed collaboration.
Ex. Social networking sites (e.g., Facebook) make it possible to develop
and maintain social connections at a different scale and intensity, and
with different organizational properties (e.g., denser
network).
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24. Efficiency of Processing
Collective efforts can lead to efficient processing.
After the 311 Earthquake, over 1500 edits on the Wikipedia article
in one day, producing a well-formed article with rich text, photos and
maps.
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25. 311 Earthquake Wikipedia Editing History
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26. Quality of Outcomes
Bounded rationality: For problem solving and decision making,
people are with limited processing resources and cannot
search the problem space thoroughly for more optimal
solutions and decisions.
Ex. Social recommendation mechanisms can help.
http://www.interaction-design.org/images/encyclopedia/social_computing/fig1_social_computing_research_social_media.jpg
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27. Human-Machine Collaboration
Human computation:
leveraging unique human
processing capabilities,
such as image and natural
language understanding
for content analysis and
labeling.
Ex. Digitizing old editions of
the New York Times
with reCAPTCHA.
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28. ESP Game
http://www.slideshare.net/ipeirotis/managing-crowdsourced-human-computation
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29. Wang
http://www.slideshare.net/ipeirotis/managing-crowdsourced-human-computation
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30. http://www.slideshare.net/ipeirotis/managing-crowdsourced-human-computation
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31. “Games With A Purpose” (GWAP)
Why are people doing the work (image labeling) for free?
• Because it’s fun!
• Image labeling as the by-product of gaming
People don’t necessarily want to do free work even when
the task is simple. Need to motivate or incentivize
people.
• Good experience (gaming, GWAP)
• Monetary incentive (Amazon Mechanical Turk)
• Education (learning, Duolingo)
Games with a Purpose http://www.gwap.com/gwap/
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32. Duolingo
Translating the whole web while people learn a second
language.
Duolingo Introduction Video
http://www.youtube.com/
watch?v=WyzJ2Qq9Abs
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33. Human-Machine Collaboration
Augmenting Human Processing: People can be bad at doing
some work, and machines can possibly help out.
Ex. IdeaExpander- Supporting idea generation by visualizing
ongoing conversations as relevant pictures.
[Wang et al., CSCW 2010] http://www.cs.cornell.edu/~haochuan/manuscripts/WangCosleyFussell_CSCW_10.pdf
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34. How to Design Social Computing Systems?
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35. Designing Social Computing Systems
Ideally from an HCI design perspective:
Study -> Design -> Prototype -> Study -> Redesign …
Human Computer Interaction
A discipline concerned with the
design implementation
evaluation
of interactive computing systems for human use
Saul Greenberg
http://pages.cpsc.ucalgary.ca/~saul/hci_topics/pdf_files/introduction_481.pdf
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36. Designing Social Computing Systems (cont.)
Realistically, designers often are not very clear what lead
to successful social computing
• Facebook changes all the time, but hard to say it’s
always becoming “better”
• Usable interfaces do not necessarily imply useful
social computing, and vice versa
• A strong “studier” culture: Studying how people
collaborate offline and online
• Borrowing from multiple disciplines: Communication,
social psychology, sociology, STS, urban planning etc.
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37. More about Social Computing Design
“Best practices and pitfalls in social computing”:
Interview with Thomas Erickson (IBM Research) on
Interaction-Design.org
Best practices (– 6’10’’):
http://www.youtube.com/watch?v=gnsRuXaZCNA
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38. Summary about Best Design Practices by Thomas Erickson
In short: It’s not trivial.
• Learning from face-to-face interaction and emulating
aspects of it online may help
• Close, in-context observation may help
• Don’t over-trust designers’ intuition
• Be comfortable with contradictions (acknowledge that
it’s complex)
• Prototype the system and push it into the context as
soon as possible
Conceptually, social computing design is still “user-
centered”, but often there is no good method or
heuristic, and the outcome can be more unpredictable than
common interface design.
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39. How: Research in Social Computing
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40. Invention-Driven and Understanding-Driven Research
Computing academics are with a strong tradition of invention
• Invent an artifact (e.g., algorithm) and study its properties
thoroughly. Invention takes a lead.
Good but don’t always work great
• Academics didn’t invent Facebook. Mark Zuckerberg and
colleagues invented the tool, but not really the social
structure and social interaction out there
• Not all clear how to initiate and sustain social networking
sites, online communities etc. yet.
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41. Invention-Driven and Understanding-Driven Research
(cont.)
Understanding-driven strategy
• Pragmatism: Doesn’t matter who invented it. Accept that
it’s there and many users like or use it.
• What’s important is not to reinvent it, but to gain deeper
understanding of the phenomena.
• Richer understanding may contribute to improvement and
new invention later.
Studying offline and online social interactions in different
domains and situations is relevant and valuable.
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42. Some Elements in Social Computing Research
Computer-mediated communication
Computer-supported cooperative work
Social media
Social networking
Online community
Human computation
Crowdsourcing
Computational social sciences (e-social sciences)
Computer-supported collaborative learning
etc.
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43. Example: What Twitter Tells Us
Computer-mediated communication
Computer-supported cooperative work
Social media
Social networking
Online community
Human computation
Crowdsourcing
Computational social sciences (e-social sciences)
Computer-supported collaborative learning
etc.
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44. “Twitterology: A New Science?”
Twitter as a micro-blogging service records hundreds of
millions public comments from hundreds of millions of
people worldwide.
• Twitter messages can possibly help us understand
people’s behaviors and answer some
social science questions
• Sampling bias:
Need to keep in mind the gap
between online and offline
behaviors
http://www.nytimes.com/2011/10/30/opinion/sunday/
twitterology-a-new-science.html
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45. Using Twitter Data to Study Mood Variation
Use a validated mood dictionary to analyze Twitter data
and present patterns of mood variation across hours of a
day and days of a week. Show that positive and negative
affect correlate with patterns of work, sleep and
daylength change.
“Global mood swing” reflected
on Twitter.
http://www.youtube.com/
watch?v=wp98_R1YieY
Scott A. Golder and Michael W. Macy.
(2011) Diurnal and Seasonal Mood Vary
with Work, Sleep and Daylength
Across Diverse Cultures. Science.
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46. The Social Aspect of Research
Communities of Practice: A profession can be defined
socially, including shared understanding, experience and
belief that people possess and things that people do in a
community. [Wenger]
http://en.wikipedia.org/wiki/Community_of_practice
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47. The Social Aspect of Research (cont.)
Social computing research is also shaped by communities.
Different communities can have somewhat different
views.
• Choosing a community, and knowing and participating it
deeply
• Things look new, different outside of the community
may look old, familiar inside the community
ACM Special Interest Group on Computer-Human
Interaction (SIGCHI)
• Two major SIGCHI conferences: CHI and CSCW.
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48. Some Major HCI Communities (Grudin, 2011)
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49. CHI (Human Factors in Computing Systems)
CHI (pronounced like “Kai”) is the umbrella conference of
SIGCHI
• One of the oldest, starting from 1982 (30 years)
• Covering all topics in HCI
• One of the largest ACM conferences, 2000-3000
participants; more than 10 parallel sessions
• One of the hardest for paper acceptance, 20-25%
acceptance rate
• Review process: external reviewers & AC (Associate Chair)
reviewers; Face-to-face PC meetings for paper selection.
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50. CHI (Human Factors in Computing Systems) 2012
Paper Subcommittees
1. Usability, Accessibility and User Experience
2. Specific Application Areas
3. Interaction Beyond the Individual
4. Design
5. Interaction Using Specific Modalities
6. Understanding People: Theory, Concepts, Methods
7. Interaction Techniques and Devices
8. Expanding Interaction through Technology, Systems and
Tools
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51. Some CHI 2012 Photos
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52. Some CHI 2012 Photos
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53. CSCW (Computer-Supported Cooperative Work)
CSCW is one SIGCHI conference specialized for collaborative
technologies and social computing.
• Held every other year (biennially) from 1986 to 2008
• Interleaving with ECSCW
• Held annually since 2010. Slight change of title to “ACM
Conference on Computer Supported Cooperative Work and Social
Computing” starting 2013.
• Similar quality and difficulty to CHI. The first SIGCHI conference
adopts a two-phase review process (similar to journal) since 2012.
• Smaller in size, about 600+ participants. More focused, easier to
socialize. Common “I liked CSCW more than CHI” comment from
CSCW and social computing folks.
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54. Reflections
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55. Be Aware of the “Because It’s New” Thinking
Intuitively, it seems straightforward to consider social computing
and HCI in general are new
• Facebook, Twitter, Apps … are new
However, many relevant ideas and systems are not new
• Email, instant messaging, BBS are useful but not new
• The underlying technical components and ideas have much
overlap
Communities are not new
• CHI, CSCW have been there for 30 years
• Understandings of social interaction and technical know-hows
are accumulating and influencing subsequent work.
Doing it because it’s valuable but not just because it’s new.
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56. The Invisible Designers
“Social design”- the Social Construction of Technology (SCOT)
• A sociological response to technological
determinism
• Social shaping of technologies.
http://ilikeinnovation.com/wp-content/uploads/2010/04/Picture-31.png
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57. The Role of Culture
Social computing cannot work without people, and people’s
thoughts and behaviors are shaped by culture (e.g.,
Western versus Eastern).
• Important to ask how local cultures differ and what’s the
implication to social computing. “One size may not fit all”
• More, perhaps we can leverage cultural characteristics and
differences to enable useful social computing.
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58. Finally, Revisiting “The Two Cultures”
C.P. Snow, British scientist and writer, argued that there
exists an intellectual and communicative gap between
“the sciences” and “the humanities”
• Scientists don’t know Shakespeare
• Humanists don’t know Thermaldynamics
• But (let’s be naive), are there any
practical, functional reasons that the
gap should be bridged?
http://www.scientificamerican.com/article.cfm?id=an-update-on-cp-snows-two-cultures
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59. Bridging the Gap Creates Value
Social computing as a proof-of-concept that combining
computing and social research, technologies and
humanities can lead to concrete, beneficial outcomes
Social studies and analyses are as useful as computer
programming in social computing design
• Viewing them as problem solving tools; creatively and
thoughtfully getting value out of them
• Merging the two cultures into one problem solving
culture- Responding to social problems, and increasing
the social contributions of work at both sides.
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60. Thank You
清華大學人機合作與社群運算實驗室
NTHU Collaborative and Social Computing Lab (CSC Lab)
http://www.cs.nthu.edu.tw/~haochuan/
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