SocioPatterns is a setup developed by Alain Barrat (CPT, Marseille, France) and Ciro Cattuto (ISI Foundation, Turin, Italy). Consisting of sensors that are worn by individuals, it allows to record close, face-to-face interactions between participants with a very high temporal resolution, during events or within buildings: schools, hospitals, etc.
As a member of the SocioPatterns collaboration, Mathieu Génois was granted the right to use the setup for research within GESIS. The setup has been deployed during the three following events (GESIS Computational Social Science Winter Symposium 2016, International Conference on Computational Social Science 2017, GESIS CSS Summer School 2017 - datasets will be available soon).
The goal is to link behavior in the physical space, as measured by the SocioPatterns setup, with data from surveys deployed during the events, in particular socio-demographic attributes and personality traits as measured by the Big Five model.
A fourth project is currently ongoing, in collaboration with the University of Helsinki, where we track interactions between first year students in physics during practical work sessions, and study whether the types of behavior are related to success in learning.