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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 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.

SUBMITTER: Rosvall M 

PROVIDER: S-EPMC2234100 | biostudies-literature | 2008 Jan

REPOSITORIES: biostudies-literature

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Maps of random walks on complex networks reveal community structure.

Rosvall Martin M   Bergstrom Carl T CT  

Proceedings of the National Academy of Sciences of the United States of America 20080123 4


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  ...[more]

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