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.
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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. https://doi.org/10.1007/978-3-642-19656-0_33
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DOI: https://doi.org/10.1007/978-3-642-19656-0_33
Publisher Name: Springer, Berlin, Heidelberg
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