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Clique Communities In Social Networks

In: Quantitative Modelling In Marketing And Management

Author

Listed:
  • Luís Cavique

    (Universidade Aberta, Portugal)

  • Armando B. Mendes

    (Universidade Açores, Portugal)

  • Jorge M.A. Santos

    (Universidade Évora, Portugal)

Abstract

There is a pressing need for new pattern recognition tools and statistical methods to quantify large graphs and predict the behaviour of network systems, due to the large amount of data which can be extracted from the web. In this work a graph mining metric, based on k-clique communities, is used, allowing a better understanding of the network structure. The proposed metric shows that for different graph families correspond different k-clique sequences.

Suggested Citation

  • Luís Cavique & Armando B. Mendes & Jorge M.A. Santos, 2012. "Clique Communities In Social Networks," World Scientific Book Chapters, in: Luiz Moutinho & Kun-Huang Huarng (ed.), Quantitative Modelling In Marketing And Management, chapter 20, pages 469-490, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789814407724_0020
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    Cited by:

    1. Harris, J. Andrew & van der Windt, Peter, 2023. "Empowering women or increasing response bias? Experimental evidence from Congo," Journal of Development Economics, Elsevier, vol. 164(C).

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