Spectral Measures of Bipartivity in Complex Networks
Statistical Mechanics
2009-11-11 v1 Physics and Society
Abstract
We introduce a quantitative measure of network bipartivity as a proportion of even to total number of closed walks in the network. Spectral graph theory is used to quantify how close to bipartite a network is and the extent to which individual nodes and edges contribute to the global network bipartivity. It is shown that the bipartivity characterizes the network structure and can be related to the efficiency of semantic or communication networks, trophic interactions in food webs, construction principles in metabolic networks, or communities in social networks.
Cite
@article{arxiv.cond-mat/0504729,
title = {Spectral Measures of Bipartivity in Complex Networks},
author = {Ernesto Estrada and Juan A. Rodriguez-Velazquez},
journal= {arXiv preprint arXiv:cond-mat/0504729},
year = {2009}
}
Comments
16 pages, 1 figure, 1 table