The Group Affect and Performance (GAP) Corpus

In this paper, we present the Group Affect and Performance (GAP) corpus, a publicly available dataset of thirteen small group meetings. The GAP corpus contains meeting audio, transcriptions, annotations, decision-making performance, as well as group member influence, post-meeting ratings of satisfaction, and demographics. In this paper, we discuss all aspects of data collection and preparation. We also present preliminary analyses and findings concerning decision-making performance, group member influence, group member satisfaction, and additional meeting characteristics. We conclude with future directions. In creating and releasing this corpus, it is our goal to stimulate research on the computational analysis of small group meetings, and to supplement the relatively small amount of currently available group interaction data.