Detection of Communities in Directed Networks based on Strongly p-Connected Components

Vincent Levorato (1, 2) , Coralie Petermann (3)

1 LIFO - Laboratoire d'Informatique Fondamentale d'Orléans
2 LINEACT - Laboratoire d'Innovation Numérique pour les Entreprises et les Apprentissages au service de la Compétitivité des Territoires
3 LAISC - Laboratoire d'informatique et des systèmes complexes

A lot of algorithms in communities detection have been proposed particularly for undirected networks. As methods to find communities in directed networks are few, our contribution is to propose a method based on strongly and unilaterally connected components, and more specifically on strongly p-connected components in directed graphs. The result is a clustering of nodes giving good results in generated graphs according to several clustering evaluation measures, and which practical time complexity remains acceptable.

Mots clés: complex networks; communities detection; graph; connected components

Domaines: Modélisation et simulation; Réseaux et télécommunications [cs.NI]

Vincent Levorato, Coralie Petermann. Detection of Communities in Directed Networks based on Strongly p-Connected Components. (CASoN), Oct 2011, Salamanca, Spain. pp.211-216. ⟨hal-00634309v2⟩