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

Social Work

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

I. Lacopini, M. Karsai, et al.

This research investigates how individuals navigate and form groups within social networks, revealing robust patterns that apply in both childhood and university settings. Conducted by Iacopo Lacopini, Márton Karsai, and Alain Barrat, this study offers valuable insights into social dynamics and proposes a dynamical model that closely mirrors real-world interactions.

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~3 min • Beginner • English
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.
Publisher
Nature Communications
Published On
Aug 27, 2024
Authors
Iacopo Lacopini, Márton Karsai, Alain Barrat
Tags
group dynamics
social networks
temporal dynamics
empirical data
interactions
higher-order networks
dynamical model
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