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Community analysis in social networks

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Abstract.

We present an empirical study of different social networks obtained from digital repositories. Our analysis reveals the community structure and provides a useful visualising technique. We investigate the scaling properties of the community size distribution, and find that all the networks exhibit power law scaling in the community size distributions with exponent either -0.5 or -1. Finally we find that the networks’ community structure is topologically self-similar using the Horton-Strahler index.

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Author information

Authors and Affiliations

  1. Departament d’Enginyeria Informática i Matemátiques, Universitat Rovira i Virgili, Avda. dels Paisos Catalans, 43006, Tarragona, Spain

    A. Arenas

  2. Department de Física Fonamental, Universitat de Barcelona, Martí i Franqués 1, 08028, Barcelona, Spain

    L. Danon, A. Díaz-Guilera & P. M. Gleiser

  3. Department of Chemical Engineering, Northwestern University, Evanston, IL, USA

    R. Guimerá

Authors
  1. A. Arenas
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  2. L. Danon
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  3. A. Díaz-Guilera
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  4. P. M. Gleiser
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  5. R. Guimerá
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Corresponding author

Correspondence to A. Díaz-Guilera.

Additional information

Received: 3 November 2003, Published online: 14 May 2004

PACS:

89.75.Fb Structures and organization in complex systems - 89.75.Da Systems obeying scaling laws - 89.75.Hc Networks and genealogical trees

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Arenas, A., Danon, L., Díaz-Guilera, A. et al. Community analysis in social networks. Eur. Phys. J. B 38, 373–380 (2004). https://doi.org/10.1140/epjb/e2004-00130-1

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  • DOI: https://doi.org/10.1140/epjb/e2004-00130-1

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