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      Tracking emerging technologies in energy research: Toward a roadmap for sustainable energy

      , , ,
      Technological Forecasting and Social Change
      Elsevier BV

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          Most cited references29

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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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            Fast algorithm for detecting community structure in networks

            M. Newman (2003)
            It has been found that many networks display community structure -- groups of vertices within which connections are dense but between which they are sparser -- and highly sensitive computer algorithms have in recent years been developed for detecting such structure. These algorithms however are computationally demanding, which limits their application to small networks. Here we describe a new algorithm which gives excellent results when tested on both computer-generated and real-world networks and is much faster, typically thousands of times faster than previous algorithms. We give several example applications, including one to a collaboration network of more than 50000 physicists.
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              Hydrogen futures: toward a sustainable energy system

              S. Dunn (2002)
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                Author and article information

                Journal
                Technological Forecasting and Social Change
                Technological Forecasting and Social Change
                Elsevier BV
                00401625
                July 2008
                July 2008
                : 75
                : 6
                : 771-782
                Article
                10.1016/j.techfore.2007.05.005
                bf206438-ca46-4649-a1a6-06f4bc3c7504
                © 2008

                http://www.elsevier.com/tdm/userlicense/1.0/

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