Combining sensors and surveys to study social interactions: A case of four science conferences

Abstract

We present a unique collection of four data sets to study social behaviour, collected during international scientific conferences. Interactions between participants were tracked using the SocioPatterns platform, which allows collecting face-to-face physical proximity events every 20 seconds. Through accompanying surveys, we gathered extensive information about the participants: sociodemographic characteristics, Big Five personality traits, DIAMONDS situation perceptions, measure of scientific attractiveness, motivations for attending the conferences, and perceptions of the crowd. Linking the sensor and survey data provides a rich window into social behaviour. At the individual level, the data sets allow personality scientists to investigate individual differences in social behaviour and pinpoint which individual characteristics (e.g., social roles, personality traits, situation perceptions) drive these individual differences. At the group level, the data allow to study the mechanisms responsible for interacting patterns within a scientific crowd during a social, networking and idea-sharing event.