| Literature DB >> 18517702 |
Brian Karrer1, Elizaveta Levina, M E J Newman.
Abstract
The discovery of community structure is a common challenge in the analysis of network data. Many methods have been proposed for finding community structure, but few have been proposed for determining whether the structure found is statistically significant or whether, conversely, it could have arisen purely as a result of chance. In this paper we show that the significance of community structure can be effectively quantified by measuring its robustness to small perturbations in network structure. We propose a suitable method for perturbing networks and a measure of the resulting change in community structure and use them to assess the significance of community structure in a variety of networks, both real and computer generated.Year: 2008 PMID: 18517702 DOI: 10.1103/PhysRevE.77.046119
Source DB: PubMed Journal: Phys Rev E Stat Nonlin Soft Matter Phys ISSN: 1539-3755