Report on SBP09 Workshop on Social Computing, Behavioral Modeling, and Prediction

Last month I attended
SBP09: Second Workshop on Social Computing, Behavioral Modeling, and Prediction in Phoenix, AZ (many thanks to Huan Liu, the organizer, for inviting me).
This is a short version of the report - full report, including a review of Reality Mining will appear in Apr 28 KDnuggets News

This workshop (SBP'09) was a single-track, two-day event attended by 108
researchers and graduate students. It was sponsored by NIH, NSF, ONR, AFOSR, and AFRL/II and in-cooperation with ACM SIGKDD.

The detailed information on the first workshop (SBP’08) (proceedings, presentations and invited speakers) can also be found at www.public.asu.edu/~huanliu/sbp08.

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The workshop started with a keynote presentation by Phillip Bonacich (UCLA, Emeritus), about Power and Exploitation in Exchange Networks:A Social-Psychological Model.

Prof. Bonacich is one of the founders of the field of social analysis and the inventor of the centrality measure [Bon87]. PageRank, independently invented by Brin and Page used Eigenvector centrality which is mathematically identical to Bonacich measure.

Prof. Bonacich nicely illustrated why network centrality is key to influence by giving an example from the Godfather movie. Godfather, a master of power wanted people to depend on him directly, so his power was measured by number of links to him, or his centrality. He stated

P(AB) = D(BA)

meaning Power of A over B is equal to dependence of B on A.

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Shade Shutters (ASU) talked about

Punishment, Rational Expectations, and Relative Payoffs.

He described the modification to the familiar prisoners dilemma, where the rational choice for each prisoner was to cooperate in either. However, the experiments where people played a version of this game showed that the actual behavior of subjects was different. The players were not maximizing their absolute "payoff", but rather the difference between their "payoff" and the other player.

Shutters argued that we should look for evolutionary biology for guidance.

Natural selection is driven by relative fitness. Thus evolutionary biology implied that assumptions of rational choice theory are not correct, and people do not maximize "absolute" payoffs, which are hard to meadure, but
relative payoffs.

This is important since international treaties are often designed to convert a dilemma to a "win-win" scenario.



If relative payoffs drive behavior then the treaty may have no effect.

He concluded that behavior in networked populations is better predicted by a biological, relative payoff model, and if relative payoffs drive behavior, restructuring payoffs may not have intended effects.

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Huan Liu, the workshop organizer has been working on data and web mining and its applications for many years, in particular Feature selection and data preprocessing.

His recent collaboration with researchers in sociology and cognitive science in social media research converges to social computing and behavioral modeling, an interdisciplinary emerging field with researchers of diverse background but shared interests. His group's recent work in this direction includes two video lectures:
1) WSDM'08 Identifying Influential Bloggers in a Community; and
2) KDD'08 Tutorial on Blogosphere: Research, Tools, and Applications.