Universal growth of social groups: empirical analysis and modeling
Ana Vrani\'c, Jelena Smiljani\'c, Marija Mitrovi\'c Dankulov

TL;DR
This paper uncovers universal growth patterns in social groups across online and offline platforms, using empirical data and a new model that combines social and random diffusion to explain group size distributions.
Contribution
It introduces a theoretical model integrating social and random diffusion processes, explaining the universal log-normal distribution of social group sizes.
Findings
Group size distributions are log-normal across datasets.
Social interactions are more influential in online group diffusion.
The proposed model accurately reproduces empirical growth patterns.
Abstract
Social groups are fundamental elements of any social system. Their emergence and evolution are closely related to the structure and dynamics of a social system. Research on social groups was primarily focused on the growth and the structure of the interaction networks of social system members and how members' group affiliation influences the evolution of these networks. The distribution of groups' size and how members join groups has not been investigated in detail. Here we combine statistical physics and complex network theory tools to analyze the distribution of group sizes in three data sets, Meetup groups based in London and New York and Reddit. We show that all three distributions exhibit log-normal behavior that indicates universal growth patterns in these systems. We propose a theoretical model that combines social and random diffusion of members between groups to simulate the…
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