March 28, 2011
Conference Paper

Bayesian Networks for Social Modeling

Abstract

This paper describes a body of work developed over the past five years. The work addresses the use of Bayesian network (BN) models for representing and predicting social/organizational behaviors. The topics covered include model construction, validation, and use. These topics show the bulk of the lifetime of such model, beginning with construction, moving to validation and other aspects of model ‘critiquing’, and finally demonstrating how the modeling approach might be used to inform policy analysis. To conclude, we discuss limitations of using BN for this activity and suggest remedies to address those limitations. The primary benefits of using a well-developed computational, mathematical, and statistical modeling structure, such as BN, are 1) there are significant computational, theoretical and capability bases on which to build 2) ability to empirically critique the model, and potentially evaluate competing models for a social/behavioral phenomena.

Revised: May 12, 2011 | Published: March 28, 2011

Citation

Whitney P.D., A.M. White, S.J. Walsh, A.C. Dalton, and A.J. Brothers. 2011. Bayesian Networks for Social Modeling. In SBP 2011: Proceedings of the 4th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, March 29-31, 2011, College Park, MD: Lecture Notes in Computer Science, edited by J Salerno, SJ Yang, D Nau and SK Chai, 6589, 227-235. Heidelberg:Springer-Verlag. PNNL-SA-76187. doi:10.1007/978-3-642-19656-0_33