Analyzing group interaction and dynamics on socio-behavioral networks of face-to-face proximity

The analysis of social interaction networks is essential for understanding and modeling network structures as well as the behavior of the involved actors. This paper describes an analysis at large scale using (sensor) data collected by RFID tags complemented by self-report data obtained using surveys. We focus on the social network of a students' freshman week, and investigate research questions concerning group behavior and structure, gender homophily, and inter-relations of sensor-based (RFID) and self-report social networks. Such analyses are a first step for enhancing interactions and enabling proactive guidance.

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