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Hybrid Community Detection in Social Networks

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Models, Algorithms and Technologies for Network Analysis (NET 2014)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 156))

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Abstract

Community detection is an important subject in the study of social networks. In this article, we point out several ideas to design hybrid methods for community detection.

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Author information

Authors and Affiliations

  1. Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China

    Hongwei Du

  2. Department of Computer Science, University of Texas at Dallas, Richardson, TX, 75080, USA

    Weili Wu, Lei Cui & Ding-Zhu Du

Authors
  1. Hongwei Du
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  2. Weili Wu
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  3. Lei Cui
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  4. Ding-Zhu Du
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Corresponding author

Correspondence to Ding-Zhu Du .

Editor information

Editors and Affiliations

  1. Laboratory of Algorithms and Technologies for Network Analysis (LATNA), National Research University Higher School of Economics, Nizhny Novgorod, Russia

    Valery A. Kalyagin

  2. Laboratory of Algorithms and Technologies for Network Analysis (LATNA), National Research University Higher School of Economics, Nizhny Novgorod, Russia

    Petr A. Koldanov

  3. Department of Industrial and System Engineering, Center for Applied Optimization University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

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© 2016 Springer International Publishing Switzerland

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Du, H., Wu, W., Cui, L., Du, DZ. (2016). Hybrid Community Detection in Social Networks. In: Kalyagin, V., Koldanov, P., Pardalos, P. (eds) Models, Algorithms and Technologies for Network Analysis. NET 2014. Springer Proceedings in Mathematics & Statistics, vol 156. Springer, Cham. https://doi.org/10.1007/978-3-319-29608-1_8

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