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Detecting complex network modularity by dynamical clustering S. Boccaletti,1

Summary: Detecting complex network modularity by dynamical clustering
S. Boccaletti,1
M. Ivanchenko,2
V. Latora,3
A. Pluchino,3
and A. Rapisarda3
CNR-Istituto dei Sistemi Complessi, Via Madonna del Piano, 10, 50019 Sesto Fiorentino (FI), Italy
and the Italian Embassy in Tel Aviv, Trade Tower, 25 Hamered Street, Tel Aviv, Israel
Department of Radiophysics, Nizhny Novgorod University, 23, Gagarin Avenue, 603600 Nizhny Novgorod, Russia
Dipartimento di Fisica e Astronomia, UniversitÓ di Catania, and INFN Sezione di Catania, Via S. Sofia, 64, 95123 Catania, Italy
Received 19 July 2006; published 12 April 2007
Based on cluster desynchronization 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 on a generic graph
with N nodes and K links.


Source: Aickelin, Uwe - School of Computer Science, University of Nottingham
Latora, Vito - Dipartimento di Fisica, Universita' di Catania


Collections: Computer Technologies and Information Sciences; Physics