Using explosive percolation in analysis of real-world networks
Disordered Systems and Neural Networks
2011-04-19 v2 Statistical Mechanics
Social and Information Networks
Physics and Society
Abstract
We apply a variant of the explosive percolation procedure to large real-world networks, and show with finite-size scaling that the university class, ordinary or explosive, of the resulting percolation transition depends on the structural properties of the network as well as the number of unoccupied links considered for comparison in our procedure. We observe that in our social networks, the percolation clusters close to the critical point are related to the community structure. This relationship is further highlighted by applying the procedure to model networks with pre-defined communities.
Cite
@article{arxiv.1010.3171,
title = {Using explosive percolation in analysis of real-world networks},
author = {Raj Kumar Pan and Mikko Kivelä and Jari Saramäki and Kimmo Kaski and János Kertész},
journal= {arXiv preprint arXiv:1010.3171},
year = {2011}
}
Comments
6 pages, 4 figures. Published version. Elongated to include the results and figures of finite-size scaling and modularity analysis