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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Community detection in complex networks via adapted Kuramoto dynamics

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Author(s):
Maia, Daniel M. N. ; de Oliveira, Joao E. M. ; Quiles, Marcos G. ; Macau, Elbert E. N.
Total Authors: 4
Document type: Journal article
Source: COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION; v. 53, p. 130-141, DEC 2017.
Web of Science Citations: 5
Abstract

Based on the Kuramoto model, a new network model, namely, the generalized Kuramoto model with Fourier term, is introduced for studying community detection in complex networks. In particular, the Fourier term provides a natural phase locking of the trajectories into a pre-defined number of clusters. A mathematical approach is used to study the behavior of the solutions and its properties. Conditions for properly choosing the coupling parameters so that phase locking takes place are presented and a quality function called clustering density is introduced to measure the effectiveness of the communities identification. Illustrations with real and synthetic networks with community structure are presented. (C) 2017 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 15/50122-0 - Dynamic phenomena in complex networks: basics and applications
Grantee:Elbert Einstein Nehrer Macau
Support type: Research Projects - Thematic Grants