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Partitioning Breaks Communities

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Mining Social Networks and Security Informatics

Part of the book series: Lecture Notes in Social Networks ((LNSN))

Abstract

Considering a clique as a conservative definition of community structure, we examine how graph partitioning algorithms interact with cliques. Many popular community-finding algorithms partition the entire graph into non-overlapping communities. We show that on a wide range of empirical networks, from different domains, significant numbers of cliques are split across the separate partitions produced by these algorithms. We then examine the largest connected component of the subgraph formed by retaining only edges in cliques, and apply partitioning strategies that explicitly minimise the number of cliques split. We further examine several modern overlapping community finding algorithms, in terms of the interaction between cliques and the communities they find, and in terms of the global overlap of the sets of communities they find. We conclude that, due to the connectedness of many networks, any community finding algorithm that produces partitions must fail to find at least some significant structures. Moreover, contrary to traditional intuition, in some empirical networks, strong ties and cliques frequently do cross community boundaries; much community structure is fundamentally overlapping and unpartitionable in nature.

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Notes

  1. 1.

    http://snap.stanford.edu/data/

  2. 2.

    Idiro Technologies.

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Acknowledgements

This work is supported by Science Foundation Ireland under grant 08/SRC/I1407: Clique: Graph and Network Analysis Cluster. An earlier version of this work appeared in ASONAM ’11 [26].

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Authors and Affiliations

  1. Clique Research Cluster, Complex Adaptive Systems Laboratory, University College Dublin, Dublin, Ireland

    Fergal Reid

  2. UCD School of Computer Science & Informatics, University College Dublin, Dublin, Ireland

    Aaron McDaid & Neil Hurley

Authors
  1. Fergal Reid
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  2. Aaron McDaid
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  3. Neil Hurley
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Corresponding author

Correspondence to Fergal Reid .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, TOBB University, Sogutozu Cad No. 43, Sogutozu Ankara, Turkey

    Tansel Özyer

  2. Information Technologies Institute, TUBITAK BILGEM, Gebze, Kocaeli, 41470, Turkey

    Zeki Erdem

  3. Computer Science, University of Calgary, University Dr. NW 2500, Calgary, T2N 1N4, Canada

    Jon Rokne

  4. American University of Sharjah, Universities City, Sharjah, Saudi Arabia

    Suheil Khoury

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Reid, F., McDaid, A., Hurley, N. (2013). Partitioning Breaks Communities. In: Özyer, T., Erdem, Z., Rokne, J., Khoury, S. (eds) Mining Social Networks and Security Informatics. Lecture Notes in Social Networks. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6359-3_5

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  • DOI: https://doi.org/10.1007/978-94-007-6359-3_5

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6358-6

  • Online ISBN: 978-94-007-6359-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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