Maps of random walks on complex networks reveal community structure
Abstract
To comprehend the multipartite organization of large-scale biological and social systems, we introduce a new information theoretic approach that reveals community structure in weighted and directed networks. The method decomposes a network into modules by optimally compressing a description of information flows on the network. The result is a map that both simplifies and highlights the regularities in the structure and their relationships. We illustrate the method by making a map of scientific communication as captured in the citation patterns of more than 6000 journals. We discover a multicentric organization with fields that vary dramatically in size and degree of integration into the network of science. Along the backbone of the network -- including physics, chemistry, molecular biology, and medicine -- information flows bidirectionally, but the map reveals a directional pattern of citation from the applied fields to the basic sciences.
Cite
@article{arxiv.0707.0609,
title = {Maps of random walks on complex networks reveal community structure},
author = {M. Rosvall and C. T. Bergstrom},
journal= {arXiv preprint arXiv:0707.0609},
year = {2008}
}
Comments
7 pages and 4 figures plus supporting material. For associated source code, see http://www.tp.umu.se/~rosvall/