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      Sustainability science: the changing landscape of sustainability research

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      Sustainability Science
      Springer Nature

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          Is Open Access

          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 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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            Environment and development. Sustainability science.

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              Key competencies in sustainability: a reference framework for academic program development

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                Author and article information

                Journal
                Sustainability Science
                Sustain Sci
                Springer Nature
                1862-4065
                1862-4057
                October 2014
                April 6 2014
                : 9
                : 4
                : 431-438
                Article
                10.1007/s11625-014-0244-x
                a0f55747-c2d0-471b-b680-90972c85fe70
                © 2014
                History

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