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      Social Information Access 

      Network-Based Social Search

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      Springer International Publishing

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          A new status index derived from sociometric analysis

          Leo Katz (1953)
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            The link-prediction problem for social networks

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              Finding and evaluating community structure in networks.

              We propose and study a set of algorithms for discovering community structure in networks-natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitive features: first, they involve iterative removal of edges from the network to split it into communities, the edges removed being identified using any one of a number of possible "betweenness" measures, and second, these measures are, crucially, recalculated after each removal. We also propose a measure for the strength of the community structure found by our algorithms, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our algorithms are highly effective at discovering community structure in both computer-generated and real-world network data, and show how they can be used to shed light on the sometimes dauntingly complex structure of networked systems.
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                Book Chapter
                2018
                May 03 2018
                : 277-309
                10.1007/978-3-319-90092-6_8
                47259e15-4daf-41f3-ba96-52b0e37eef84
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