In this paper, we present a unique collection of four data sets to study social behaviour. The data were collected at four international scientific conferences, during which we measured face-to-face contacts along with additional information about individuals. Building on innovative methods developed in the last decade to study human social behaviour, interactions between participants were monitored using the SocioPatterns platform, which allows collecting face-to-face physical proximity events every 20 seconds in a well-defined social context. Through accompanying surveys, we gathered extensive information about the participants, including sociodemographic characteristics, Big Five personality traits, DIAMONDS situational perceptions, measure of scientific attractiveness, motivations for attending the conferences, and perceptions of the crowd (e.g., in terms of gender distribution). 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, situational perceptions) drive these individual differences. At the group level, the data also allow studying the mechanisms responsible for interacting patterns within a scientific crowd during a social, networking and idea-sharing event. The data are available for secondary analysis.