Measuring group cohesion as a factor in collaborative decision making

Abstract: We define group cohesion as a general consistency in group objectives or values over time that encompasses an overall persistence in the cooperative nature of the members’ interactions. This characterization applies primarily to task-oriented teams, although it may also be used more broadly to purpose-driven groups.We have developed a collection of AI tools that can estimate the degree of group cohesion by measuring the quality of interaction between group members. To compute this assessment, we identify a series of sociolinguistic behaviors, both individual and collective, that obtain within the group as reflected in the members’ utterances. Individual behaviors impacting group cohesion include agenda control, involvement, agreement and disagreement; relevant collective behaviors include the balance of agreement-disagreement, sociability, and task focus. Estimating distribution and degree of these behaviors are required to assess the character of members’ relations and the consistency of group’s objective. In this paper we focus on collective behaviors, and how they can be automatically computed from group interactions. Implementation of individual behaviors can be found in (Broadwell et al., 2013).One measure of group cohesion is a degree of task focus among the group members. It is a collective behavior that can be measured by the degree to which the discussion is focused on a shared objective, as well as by the efficiency with which the group works towards this objective. The efficiency of this progress is evidenced by the degree to which the discourse stays on topic with few off-topic digressions. Another measure of group cohesion is persistence of roles (Bales, 2001), which tracks whether certain key social functions in the group, such as leadership, persist throughout the discourse, though not necessarily filled continuously by the same individuals. A cohesive group is also characterized by a high degree of sociability. This includes adherence to general conversational principles, which are in turn reflected by certain sequences of dialogue acts, i.e., question-answer, offer-response, as well as sequences of expressions classified as conversational norms, including greetings, thanks and apologies. Groups with higher values of the sociability behavior are considered more cohesive.In this paper we discuss a practical implementation of an AI system that can determine cohesiveness of a group engaged in task-oriented discussion.* Bales, Robert Freed (2001) Social Interaction Systems, Theory and Measurement, Transaction Pub.* George Aaron Broadwell, Jennifer Stromer-Galley, Tomek Strzalkowski, Sarah Taylor, Umit Boz, Samira Shaikh, Liu Ting, and Nick Webb (2013) Modeling Socio-Cultural Phenomena in Discourse. Journal of Natural Language Engineering. 19(2): 213-257. Cambridge

Keywords: social computing, collaborative decision making

DOI: 10.54941/ahfe1006932

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