Affective Dynamics and Control in Group Processes

Authors: Jesse Hoey Tobias Schröder Jonathan H. Morgan Kimberly B. Rogers Meiyappan Nagappan

Venue: Group Interaction Frontiers in Technology, 2018

Year: 2018

Abstract: 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 behaviour, and attempted to link to social structures. However, these models make simplifying assumptions about human understanding of culture that are of ten 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.

BibTeX:

@inproceedings{jessehoey2018adacigp,
    author = "Jesse Hoey and Tobias Schröder and Jonathan H. Morgan and Kimberly B. Rogers and Meiyappan Nagappan",
    title = "Affective Dynamics and Control in Group Processes",
    year = "2018",
    booktitle = "Proceedings of the Group Interaction Frontiers in Technology"
}

Plain Text:

Jesse Hoey, Tobias Schröder, Jonathan H. Morgan, Kimberly B. Rogers, and Meiyappan Nagappan, "Affective Dynamics and Control in Group Processes," Group Interaction Frontiers in Technology