Using the Clustering Coefficient to Guide a Genetic-Based Communities Finding Algorithm

  • Gema Bello
  • Héctor Menéndez
  • David Camacho
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6936)


Finding communities in networks is a hot topic in several research areas like social network, graph theory or sociology among others. This work considers the community finding problem as a clustering problem where an evolutionary approach can provide a new method to find overlapping and stable communities in a graph. We apply some clustering concepts to search for new solutions that use new simple fitness functions which combine network properties with the clustering coefficient of the graph. Finally, our approach has been applied to the Eurovision contest dataset, a well-known social-based data network, to show how communities can be found using our method.


clustering coefficient social networks community finding genetic algorithms 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Gema Bello
    • 1
  • Héctor Menéndez
    • 1
  • David Camacho
    • 1
  1. 1.Departamento de Ingeniería Informática, Escuela Politécnica SuperiorUniversidad Autónoma de MadridMadridSpain

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