Maps of random walks on complex networks reveal community structure

@article{citeulike:2283763, 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 networkincluding physics, chemistry, molecular biology, and medicineinformation flows bidirectionally, but the map reveals a directional pattern of citation from the applied fields to the basic sciences. 10.1073/pnas.0706851105}, author = {Rosvall, Martin and Bergstrom, Carl T. }, citeulike-article-id = {2283763}, doi = {10.1073/pnas.0706851105}, journal = {Proceedings of the National Academy of Sciences}, keywords = {analysis, clip2, network}, month = {January}, pages = {0706851105+}, posted-at = {2008-02-13 09:02:16}, priority = {2}, title = {Maps of random walks on complex networks reveal community structure}, url = {http://dx.doi.org/10.1073/pnas.0706851105}, year = {2008} }

TY - JOUR ID - citeulike:2283763 L3 - citeulike-article-id:2283763 TI - Maps of random walks on complex networks reveal community structure JF - Proceedings of the National Academy of Sciences SP - 0706851105 N2 - 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 networkincluding physics, chemistry, molecular biology, and medicineinformation flows bidirectionally, but the map reveals a directional pattern of citation from the applied fields to the basic sciences. 10.1073/pnas.0706851105 KW - analysis KW - clip2 KW - network AU - Rosvall, Martin AU - Bergstrom, Carl PY - 2008/01/23/ UR - http://dx.doi.org/10.1073/pnas.0706851105 ER -