A mean-field analysis of community structure in social and kin networks
E. Durand, M. G. B Blum, O. Francois
Abstract
We provide a mean-field analysis of community structure of social and biological networks assuming that actors are able to evaluate some tree-derived distance to the other actors and tend to aggregate with the less distant. We show that such networks have small components, and give exact descriptions for the probability distribution of a typical community size and the number of communities. In particular, we show that the probability distribution of the community size is well-approximated by a power-law distribution with exponent two. We illustrate the robustness of the mean-field analysis by comparing its predictions on previously studied social networks and biological data.
Create a lesson
Related papers
Reservoir: A Large-Scale Simulated Dataset for Training and Evaluating Epidemiological Models
Carson Dudley, Reiden Magdaleno, Marisa Eisenberg
What sets the critical genome length for sympatric speciation? A closed form and asymptotic theory
Dan Braha, Marcus A. M. de Aguiar, Vitor M. Marquioni
The emergence and evolution of a referential code in populations of bee-like agents
Grzegorz Chrupała
Tree Buckets and the Reconstruction of Pairs of Phylogenetic Trees
Sky Basire, Michael Hendriksen
Global geometry of the genotype-phenotype map illuminates a trade-off between penetrance and mutational adaptability
Yutaro Ikeda, Kunihiko Kaneko, Tetsuhiro S. Hatakeyama
The Informational Model of the Holobiont: Statistical Tests for Selection and Extension to a Theory of Variable Interactions
Antonio Carvajal-Rodríguez