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      Maps of random walks on complex networks reveal community structure

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      Proceedings of the National Academy of Sciences
      Proceedings of the National Academy of Sciences

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          Abstract

          <p class="first" id="d975395e63">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 &gt;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. </p>

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          Author and article information

          Journal
          Proceedings of the National Academy of Sciences
          Proceedings of the National Academy of Sciences
          Proceedings of the National Academy of Sciences
          0027-8424
          1091-6490
          January 29 2008
          January 29 2008
          January 23 2008
          January 29 2008
          : 105
          : 4
          : 1118-1123
          Article
          10.1073/pnas.0706851105
          2234100
          18216267
          9b670360-b749-4951-9f00-c2545093def7
          © 2008
          History

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