The temporal dynamics of group interactions in higher-order social networks

TL;DR

This paper investigates the temporal dynamics of group interactions in higher-order social networks, revealing consistent patterns in how individuals navigate and groups form or disband, supported by empirical data and a new dynamical model.

Contribution

It introduces a dynamical model that accurately reproduces observed group formation and disaggregation patterns in higher-order social networks based on empirical data.

Findings

Robust patterns in group formation and disaggregation across contexts

A dynamical model closely matches empirical observations

Insights into individual navigation and group evolution mechanisms

Abstract

Representing social systems as networks, starting from the interactions between individuals, sheds light on the mechanisms governing their dynamics. However, networks encode only pairwise interactions, while most social interactions occur among groups of individuals, requiring higher-order network representations. Despite the recent interest in higher-order networks, little is known about the mechanisms that govern the formation and evolution of groups, and how people move between groups. Here, we leverage empirical data on social interactions among children and university students to study their temporal dynamics at both individual and group levels, characterising how individuals navigate groups and how groups form and disaggregate. We find robust patterns across contexts and propose a dynamical model that closely reproduces empirical observations. These results represent a further step in understanding social systems, and open up research directions to study the impact of group dynamics on dynamical processes that evolve on top of them.