Maps of random walks on complex networks reveal community structure

Details Maps of random walks on complex networks reveal community structure Maps of random walks on complex networks reveal community structure

2007-07-04

arxiv.org/abs/0707.0609v3

PNAS 105, 1118-1123 (2008)

Physics

Physics and Society

7 pages and 4 figures plus supporting material. For associated source code, see http://www.tp.umu.se/~rosvall/

Scientific paper

10.1073/pnas.0706851105

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.

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