Automated mapping of competitive and collaborative overlapping talk in video meetings.

Abstract

Video meetings are notorious for difficulties with conversational turn-taking, which has impacts on inclusion and outcomes. We present a scalable automatic process to categorize turn-taking patterns in remote meetings based on eyes-off analysis of meeting transcripts. Drawing on a series of remote meetings (10 series, 34 total meetings) recorded in July-August 2021 by employees of a global technology company, we identified and parametrized patterns of cooperative and competitive overlaps of turns. The results show initial success characterizing people's behaviours as either likely to continue or cede turns based on either the amount of overlap that they produce during other's turns or the amount of overlap they experience in their own turns. With further development and validation, this method could be used to measure inclusion in remote and hybrid meetings.

Tasks

Reproductions