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Proc Natl Acad Sci U S A. 2008 Jan 29;105(4):1118-23. doi: 10.1073/pnas.0706851105. Epub 2008 Jan 23.

Maps of random walks on complex networks reveal community structure.

Author information

  • 1Department of Biology, University of Washington, Seattle, WA 98195-1800, USA. rosvall@u.washington.edu

Abstract

To comprehend the multipartite organization of large-scale biological and social systems, we introduce an information theoretic approach that reveals community structure in weighted and directed networks. We use the probability flow of random walks on a network as a proxy for information flows in the real system and decompose the network into modules by compressing a description of the probability flow. 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 >6,000 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.

PMID:
18216267
[PubMed - indexed for MEDLINE]
PMCID:
PMC2234100
Free PMC Article

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