Bayesian Networks for Social Modeling

  • Paul Whitney
  • Amanda White
  • Stephen Walsh
  • Angela Dalton
  • Alan Brothers
Conference paper

DOI: 10.1007/978-3-642-19656-0_33

Volume 6589 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Whitney P., White A., Walsh S., Dalton A., Brothers A. (2011) Bayesian Networks for Social Modeling. In: Salerno J., Yang S.J., Nau D., Chai SK. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2011. Lecture Notes in Computer Science, vol 6589. Springer, Berlin, Heidelberg

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. 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) the ability to empirically critique the model, and potentially evaluate competing models for a social/behavioral phenomenon.

Keywords

Social modeling calibration validation diagnostics expert elicitation evidence assessment 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Paul Whitney
    • 1
  • Amanda White
    • 1
  • Stephen Walsh
    • 1
  • Angela Dalton
    • 1
  • Alan Brothers
    • 1
  1. 1.Pacific Northwest National LaboratoryRichlandUSA