English

Detection of Complex Networks Modularity by Dynamical Clustering

Physics and Society 2015-06-26 v3 Statistical Mechanics Computational Physics

Abstract

Based on cluster de-synchronization properties of phase oscillators, we introduce an efficient method for the detection and identification of modules in complex networks. The performance of the algorithm is tested on computer generated and real-world networks whose modular structure is already known or has been studied by means of other methods. The algorithm attains a high level of precision, especially when the modular units are very mixed and hardly detectable by the other methods, with a computational effort O(KN){\cal O}(KN) on a generic graph with NN nodes and KK links.

Keywords

Cite

@article{arxiv.physics/0607179,
  title  = {Detection of Complex Networks Modularity by Dynamical Clustering},
  author = {S. Boccaletti and M. Ivanchenko and V. Latora and A. Pluchino and A. Rapisarda},
  journal= {arXiv preprint arXiv:physics/0607179},
  year   = {2015}
}

Comments

5 pages, 2 figures. Version accepted for publication on PRE Rapid Communications: figures changed and text added