  Human social interactions in local settings can be experimentally detected by
recording the physical proximity and orientation of people. Such interactions,
approximating face-to-face communications, can be effectively represented as
time varying social networks with links being unceasingly created and destroyed
over time. Traditional analyses of temporal networks have addressed mostly
pairwise interactions, where links describe dyadic connections among
individuals. However, many network dynamics are hardly ascribable to pairwise
settings but often comprise larger groups, which are better described by
higher-order interactions. Here we investigate the higher-order organizations
of temporal social networks by analyzing three publicly available datasets
collected in different social settings. We find that higher-order interactions
are ubiquitous and, similarly to their pairwise counterparts, characterized by
heterogeneous dynamics, with bursty trains of rapidly recurring higher-order
events separated by long periods of inactivity. We investigate the evolution
and formation of groups by looking at the transition rates between different
higher-order structures. We find that in more spontaneous social settings,
group are characterized by slower formation and disaggregation, while in work
settings these phenomena are more abrupt, possibly reflecting pre-organized
social dynamics. Finally, we observe temporal reinforcement suggesting that the
longer a group stays together the higher the probability that the same
interaction pattern persist in the future. Our findings suggest the importance
of considering the higher-order structure of social interactions when
investigating human temporal dynamics.
