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Comparison and validation of community structures in complex networks

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  • Gustafsson, Mika
  • Hörnquist, Michael
  • Lombardi, Anna

Abstract

The issue of partitioning a network into communities has attracted a great deal of attention recently. Most authors seem to equate this issue with the one of finding the maximum value of the modularity, as defined by Newman. Since the problem formulated this way is believed to be NP-hard, most effort has gone into the construction of search algorithms, and less to the question of other measures of community structures, similarities between various partitionings and the validation with respect to external information.

Suggested Citation

  • Gustafsson, Mika & Hörnquist, Michael & Lombardi, Anna, 2006. "Comparison and validation of community structures in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 559-576.
    • Handle: RePEc:eee:phsmap:v:367:y:2006:i:c:p:559-576
    DOI: 10.1016/j.physa.2005.12.017
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    References listed on IDEAS

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    1. Glenn Milligan, 1981. "A monte carlo study of thirty internal criterion measures for cluster analysis," Psychometrika, Springer;The Psychometric Society, vol. 46(2), pages 187-199, June.
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    Cited by:

    1. Chang, Y.F. & Han, S.K. & Wang, X.D., 2018. "The way to uncover community structure with core and diversity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 111-119.
    2. Ma, Xiaoke & Gao, Lin & Yong, Xuerong & Fu, Lidong, 2010. "Semi-supervised clustering algorithm for community structure detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 187-197.

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