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      The research space: using career paths to predict the evolution of the research output of individuals, institutions, and nations

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          Is Open Access

          Maps of random walks on complex networks reveal community structure

          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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            Mapping the backbone of science

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              Visualizing science by citation mapping

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                Author and article information

                Journal
                Scientometrics
                Scientometrics
                Springer Nature
                0138-9130
                1588-2861
                December 2016
                September 2016
                : 109
                : 3
                : 1695-1709
                Article
                10.1007/s11192-016-2125-9
                27a14558-b4c1-4c81-875b-d7dffa69d4b4
                © 2016
                History

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