Abstract
Small group researchers are increasingly called to engage the computational sciences. One challenge in answering this call is the lack of information concerning what the study of small groups looks like in these domains. This paper addresses this challenge through a prospecting review of research that computationally models or trains computers to learn small group and team behavior and is published in computing disciplines from 2016 to 2023. This review investigated how groups were modeled, for what purpose, what group elements were modeled, and whether social science informed the model design. Qualitative methods were used to analyze 119 published articles. Suggestions are presented for increasing the influence of small group research on the computational modeling of groups and teams, particularly for researchers with limited access to large research teams or resources. This review helps bridge the gap between small group research and computational sciences to advance the understanding of small groups and teams.
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