Finding instabilities in the community structure of complex networks

David Gfeller, Jean-Cédric Chappelier, and Paolo De Los Rios
Phys. Rev. E 72, 056135 – Published 29 November 2005

Abstract

The problem of finding clusters in complex networks has been studied by mathematicians, computer scientists, and, more recently, by physicists. Many of the existing algorithms partition a network into clear clusters without overlap. Here we introduce a method to identify the nodes lying “between clusters,” allowing for a general measure of the stability of the clusters. This is done by adding noise over the edge weights. Our method can in principle be used with almost any clustering algorithm able to deal with weighted networks. We present several applications on real-world networks using two different clustering algorithms.

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  • Received 30 March 2005

DOI:https://doi.org/10.1103/PhysRevE.72.056135

©2005 American Physical Society

Authors & Affiliations

David Gfeller1, Jean-Cédric Chappelier2, and Paolo De Los Rios1

  • 1Laboratoire de Biophysique Statistique, SB/ITP, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
  • 2School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland

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Issue

Vol. 72, Iss. 5 — November 2005

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