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Kirchhoff Centrality Measure for Collaboration Network

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Computational Social Networks (CSoNet 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9795))

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Abstract

This paper extends the concept of betweenness centrality based on Kirchhoff’s law for electric circuits from centrality of nodes to centrality of edges. It is shown that this new measure admits analytical definition for some classes of networks such as bipartite graphs, with computation for larger networks. This measure is applied for detecting community structure within networks. The results of numerical experiments for some examples of networks, in particular, Math-Net.ru (a Web portal of mathematical publications) are presented, and a comparison with PageRank is given.

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Acknowledgements

This research was supported by the Russian Foundation for Basic Research (project no. 16-51-55006), the Russian Humanitarian Science Foundation (project no. 15-02-00352) and the Division of Mathematical Sciences of the Russian Academy of Sciences.

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Authors and Affiliations

  1. Institute of Applied Mathematical Research, Karelian Research Center, Russian Academy of Sciences, 11, Pushkinskaya St., Petrozavodsk, Russia, 185910

    Vladimir V. Mazalov

  2. Transbaikal State University, 30, Aleksandro-Zavodskaya St., Chita, Russia, 672039

    Bulat T. Tsynguev

Authors
  1. Vladimir V. Mazalov
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  2. Bulat T. Tsynguev
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Correspondence to Vladimir V. Mazalov .

Editor information

Editors and Affiliations

  1. Ton Duc Thang University , Ho Chi Minh City, Vietnam

    Hien T. Nguyen

  2. VSB-Technical University of Ostrava , Ostrava, Poland

    Vaclav Snasel

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© 2016 Springer International Publishing Switzerland

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Mazalov, V.V., Tsynguev, B.T. (2016). Kirchhoff Centrality Measure for Collaboration Network. In: Nguyen, H., Snasel, V. (eds) Computational Social Networks. CSoNet 2016. Lecture Notes in Computer Science(), vol 9795. Springer, Cham. https://doi.org/10.1007/978-3-319-42345-6_13

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  • DOI: https://doi.org/10.1007/978-3-319-42345-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42344-9

  • Online ISBN: 978-3-319-42345-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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