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Title: Affective Dynamics and Control in Group Processes
The computational modeling of groups requires models that connect micro-level with macro-level processes and outcomes. Recent research in computational social science has started from simple models of human behavior, and attempted to link to social structures. However, these models make simplifying assumptions about human understanding of culture that are often not realistic and may be limiting in their generality. In this paper, we present work on Bayesian affect control theory as a more comprehensive, yet highly parsimonious model that integrates artificial intelligence, social psychology, and emotions into a single predictive model of human activities in groups. We illustrate these developments with examples from an ongoing research project aimed at computational analysis of virtual software development teams.  more » « less
Award ID(s):
1723608
PAR ID:
10135898
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Group Interaction Frontiers in Technology; Association for Computing Machinery
Page Range / eLocation ID:
1 to 7
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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