Community detection in multiplex networks: A seed-centric approach

Manel Hmimida; Rushed Kanawati

doi:10.3934/nhm.2015.10.71

Article Contents

2015, Volume 10, Issue 1: 71-85. Doi: 10.3934/nhm.2015.10.71

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Community detection in multiplex networks: A seed-centric approach

Manel Hmimida^1, and
Rushed Kanawati^2,

1.
DICEN-CNAM 292, rue St Martin, 75141 PARIS CEDEX 03, & & LIPN - CNRS UMR 7030, Paris
2.
PSC, UP13, LIPN, CNRS UMR 7030, Villetaneuse

Received: July 2014

Revised: December 2014

Published: March 2015

Abstract / Introduction Related Papers Cited by

Abstract

Multiplex network is an emergent model that has been lately proposed in order to cope with the complexity of real-world networks. A multiplex network is defined as a multi-layer interconnected graph. Each layer contains the same set of nodes but interconnected by different types of links. This rich representation model requires to redefine most of the existing network analysis algorithms. In this paper we focus on the central problem of community detection. Most of existing approaches consist on transforming the problem, in a way or another, to the classical setting of community detection in a monoplex network. In this work, we propose a new approach that consists on adapting a seed-centric algorithm to the multiplex case. The first experiments on heterogeneous bibliographical networks show the relevance of the approach compared to the existing algorithms.

Keywords:

Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C35.

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