Higher-order structures in face-to-face interaction networks

Face-to-face interactions in human gatherings have a significant impact in various contexts, including disease spreading and opinion dynamics. In this thesis, we investigate the temporal properties of group interactions in different settings using data recorded using the SocioPatterns platform. Our analysis focuses on higher-order structures, revealing that the distributions of group durations exhibit large tails, indicating the absence of a typical time scale for higher-order interactions in human gatherings. By examining the accompanying metadata associated with the contact data, we explore the role of homophily, which refers to the tendency of individuals to interact with others with whom share similar attributes, in face-to-face interactions. Interestingly, our findings demonstrate that the presence of higher-order homophily is possible even in social settings where the corresponding low-order homophily is absent. To better understand these dynamics, we present a simple model for human face-to-face interactions. This initial model fails to accurately reproduce the higher-order temporal statistics observed in the data. As a solution, we present a modified version of the model that successfully captures both levels of the empirical temporal statistics. The insights gained from this research provide a valuable foundation for future studies aiming to uncover the fundamental properties of human interactions. The exploration of higher-order structures and homophily holds great potential in deepening our understanding of the complex dynamics inherent in face-to-face interactions.