Emergence of clustering, correlations, and communities in a social network model
Statistical Mechanics
2007-05-23 v2 Disordered Systems and Neural Networks
Abstract
We propose a simple model of social network formation that parameterizes the tendency to establish acquaintances by the relative distance in a representative social space. By means of analytical calculations and numerical simulations, we show that the model reproduces the main characteristics of real social networks: non- vanishing clustering coefficient, assortative degree correlations, and the emergence of a hierarchy of communities. Our results highlight the importance of communities in the understanding of the structure of social networks.
Keywords
Cite
@article{arxiv.cond-mat/0309263,
title = {Emergence of clustering, correlations, and communities in a social network model},
author = {Marian Boguna and Romualdo Pastor-Satorras and Albert Diaz-Guilera and Alex Arenas},
journal= {arXiv preprint arXiv:cond-mat/0309263},
year = {2007}
}