Social computing is an interdisciplinary field that studies how technology can facilitate social interaction and communication. It has three main goals: 1) Develop better social software to facilitate online interaction; 2) Computerize aspects of human society through modeling and simulation; 3) Forecast how changing technologies may impact social behavior. Social computing draws from fields like sociology, computer science, and applied physics. It covers topics such as social networks, recommendation systems, virtual worlds, and using technology to study social dynamics. Methods include social network analysis, simulation, and data mining of social media. Learning social computing would help information scientists develop technologies that consider social factors and behaviors.

1. Social computing

2. [ Q ]
What is Social computing?

4. source Definition
Communications of the
ACM
Describing any type of computing application in which
software serves as an intermediary or a focus for
a social relation
Wikipedia (http://
en.wikipedia.org/wiki/
Social_computing)
Referring to the use of social software, a growing
trend in ICT usage of tools that support social inter-
action and communication
Forrester Research
A social structure in which technology puts power in
individuals and communities, not institutions
Wang et al.
(2007)’s definition
Computational facilitation of social
studies and human social dynamics as
well as the design and use of ICTs that
consider social context

5. Agent
Modeling

6. Goals
•Develop better social softwares to
facilitate interaction and
communication among groups of
people
•Computerize aspects of human
society
•Forecast the effects of changing
technologies and policies on social
and cultural behavior.
* Wang, F.Y., Zeng, D., Carley, K.M., & Mao, W. (2007).
Social computing: From social informatics to social intelligence. IEEE Intelligent Systems, 22(2), 79-83.

7. •Social network sites: Facebook
•Recommendation
•Social network analysis
•Community
•Open sensing and privacy
•Ecology
•Trend analysis
•Simulation
•Virtual worlds as a social space
•Opinion sentimental analysis
•Social visualization
Scope

8. •Social recommendation
•ICTs e.g., e-mail, Skype, handout, Line
•Social network sites: Facebook
•Lifelogging & privacy
•Virtual worlds as a social space
Topics

9. Methods
• Social network analysis
• Community
• Trend analysis
• Social Simulation
• Ecological Analysis
• Opinion sentimental analysis
• SocialVisualization

10. •
•
•

11. Social
recommendation?
community or
network?

13. Sociology -
Social network theories
Applied Physics -
Small World
Applied Physics
- Chaos,
complexity
Sociology -
Simulation

14. Local-scale
Recommendation
Global-scale

15. With closed tastes

17. Social Network Sites
Social computing> Social Network Sites

18. •Networked
•Acquaintance-based
hard to social networking
•Clustered
•ego-centric
•Asynchronous
multiplay
Social computing> Social Network Sites

19. •From surfer to householder
(geo-center)
•Communities based on social
network
Ptolemy Model

20. Virtual worlds as artificial
societies

22. 1 - 30 30 - 60 60 - 120 120 - 240 240 - 4800
0
1 - 30
30 - 45
45 - 60
60
AverageLevelsofGuildMembers
Number of Guild Members
4
20
48
2.5 5 6
11.5 3 0.5
0.010.51
2.5
42 2
8
1 - 30 30 - 60 60 - 120 120 - 240 240 - 4800
0
1 - 30
30 - 45
45 - 60
60
AverageLevelsofGuildMembers
Number of Guild Members

23. 1 - 30 30 - 60 60 - 120 120 - 240 240 - 4800
0
1 - 30
30 - 45
45 - 60
60
AverageLevelsofGuildMembers
Number of Guild Members
LV6/32
1 - 30 30 - 60 60 - 120 120 - 240 240 - 4800
0
1 - 30
30 - 45
45 - 60
60

24. New
Guild 1 - 30 30 - 60 60 - 120 120 - 240 240 - 480
0
0
1 - 10
10 - 20
40 - 50
New
Guild
Small
Guild Newbie
Guild
Elite
Guild
Unstable
Guild
AverageLevelsofGuildMembers
Number of Guild Members
Dismissing
Advancing
20 - 30
30 - 40
50 - 60
60 - 70 Big
Guild
1 - 30 30 - 60 60 - 120 120 - 240 240 - 480
0
0
1 - 10
10 - 20
40 - 50
Newbie
Guild
AverageLevelsofGuildMembers
Number of Guild Members
20 - 30
30 - 40
50 - 60
60 - 70
Following
New
Guild
Small
Guild
Big
Guild
Elite
Guild
Unstable
Guild

25. 1 - 30 30 - 60 60 - 120 120 - 240 240 - 480
0
0
1 - 10
10 - 20
40 - 50
Newbie
Guild
AverageLevelsofGuildMembers
Number of Guild Members
20 - 30
30 - 40
50 - 60
60 - 70
Following
Dismissing
Advancing
New
Guild
Small
Guild
Big
Guild
Elite
Guild
Unstable
Guild
1 - 30 30 - 60 60 - 120 120 - 240 240 - 480
0
0
1 - 10
10 - 20
40 - 50
New
Guild
Small
Guild
Big
Guild
Newbie
Guild
Elite
Guild
Unstable
Guild
AverageLevelsofGuildMembers
Number of Guild Members
Quit Guild Play
but Stay in Game
20 - 30
30 - 40
50 - 60
60 - 70

27. Characters
Behaviors
Characters
Behaviors
Characters
Behaviors
Characters
Behaviors
Characters
Behaviors
Network self
Connected, Intermediated
Real self
Virtual self
Intermediated, represented

28. Modeling & Simulation
Social computing> Simulation

29. Stable-Marriage Problem
•
Stable-Marriage
•
Stable
•
Social computing> Simulation

30. The Gale-Shapley algorithm
for stable matching
•
•
•
Lloyd Shapley Alvin Roth
Social computing> Simulation

31. • Roth,A.E. & Shapley, L.S. (2012). Stable allocation and the practice of market design.
Nobel Price Scientific Background. http://www.nobelprize.org/nobel_prizes/economics/laureates/2012/advanced-
economicsciences2012.pdf
• Hills,T. & Todd, P. (2008). Population Heterogeneity and Individual Differences in an
Assortative Agent-Based Marriage and Divorce Model (MADAM) Using Search with
Relaxing Expectations. Journal of Artificial Societies and Social Simulation 11(4)5
<http://jasss.soc.surrey.ac.uk/11/4/5.html>.
• Novikoff,T. P., Kleinberg, J. M., & Strogatz, S. H. (2012). Education of a model student.
Proceedings of the National Academy of Sciences, 109(6), 1868-1873.
Social computing> Simulation

32. 42/50
(1)(2) (3) (4) (5)
(1)
(2)
(3)
(4)
(5)
Social computing> Simulation

33. Social computing> Simulation

34. Stroud, P., Del Valle, S., Sydoriak, S., Riese, J., & Mniszewski, S. (2007). Spatial dynamics of pandemic influenza in a massive artificial society. Journal of
Artificial Societies and Social Simulation, 10(4), 9.
Social computing> Simulation

35. 2010/01 2011/01 2012/01
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37. 2~3 weeks delay

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PredictedTraining

40. Life logging

41. Christine, R. (2009) Tracking life in graphic detail.The Wall Street Journal, http://online.wsj.com/article/SB124537742433730231.html

43. 2010

44. Sentiment Analysis
Samsungios
http://fbwatcher-t.opview.com.tw/Account/Login?returnUrl=%2F

45. Course Requirements

46. Works
•Leading 1 paper discussion
•Taking course notes for 10 weeks
•2 take-home assignments for social network analysis
•Final Projects

47. Grading Policy
•1 presentation 20%
•1 final projects 45%
•2 social network analysis assignments 20%
•3 notes 15%

48. No response, No insight

49. [Q]
Why information scientists
should learn social computing?