Abstract
Models seeking to predict human social behavior must contend with multiple sources of individual and group variability that underlie social behavior. One set of interrelated factors that strongly contribute to that variability – motivations, personality, and emotions – has been only minimally incorporated in previous computational models of social behavior. The Personality, Affect, Culture (PAC) framework is a theory-based computational model that addresses this gap. PAC is used to simulate social agents whose social behavior varies according to their personalities and emotions, which, in turn, vary according to their motivations and underlying motive control parameters. Examples involving disease spread and counter-insurgency operations show how PAC can be used to study behavioral variability in different social contexts.
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Miller, L.C., Read, S.J., Zachary, W., Rosoff, A. (2010). Modeling the Impact of Motivation, Personality, and Emotion on Social Behavior. In: Chai, SK., Salerno, J.J., Mabry, P.L. (eds) Advances in Social Computing. SBP 2010. Lecture Notes in Computer Science, vol 6007. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12079-4_37
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DOI: https://doi.org/10.1007/978-3-642-12079-4_37
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