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Dual modularity optimization for detecting overlapping communities in bipartite networks

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Abstract

Many algorithms have been designed to discover community structure in networks. These algorithms are mostly dedicated to detecting disjoint communities. Very few of them are intended to discover overlapping communities, particularly the bipartite networks have hardly been explored for the detection of such communities. In this paper, we describe a new approach which consists in forming overlapping mixed communities in a bipartite network based on dual optimization of modularity. To this end, we propose two algorithms. The first one is an evolutionary algorithm dedicated for global optimization of the Newman’s modularity on the line graph. This algorithm has been tested on well-known real benchmark networks and compared with several other existing methods of community detection in networks. The second one is an algorithm that locally optimizes the graph Mancoridis modularity, and we have adapted to a bipartite graph. Specifically, this second algorithm is applied to the decomposition of vertices, resulting from the evolutionary process, and also characterizes the overlapping communities taking into account their semantic aspect. Our approach requires a priori no knowledge on the number of communities searched in the network. We show its interest on two datasets, namely, a group of synthetic networks and real-world network whose structure is also difficult to understand.

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Notes

  1. \(|V|\) represents the number of elements in the set \(V\).

  2. http://sites.google.com/site/santofortunato/inthepress2.

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Acknowledgments

We thank the editor and anonymous reviewers for their useful comments and valuable guidance. I thank Mr. Mustapha Lebbah Professor and Researcher at the University of Paris 13 for his valuable assistance, particularly for the means at my disposal during periods of internships within the team \(A3\) of LIPN, Paris 13 University. I warmly thank Mr. Mohand-Saïd Souam, University Professor at the Université Paris Ouest Nanterre La Defense, that I will not forget the valuable moral support he gave me. I fraternally thank him for the constant interest he has consistently shown to me during the writing of this article.

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Authors and Affiliations

  1. UMMTO University of Tizi-Ouzou, Tizi Ouzou, Algeria

    Fatiha Souam & Ali Aïtelhadj

  2. USTHB University of Algiers, Algiers, Algeria

    Riadh Baba-Ali

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  1. Fatiha Souam
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  2. Ali Aïtelhadj
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  3. Riadh Baba-Ali
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Correspondence to Fatiha Souam.

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Souam, F., Aïtelhadj, A. & Baba-Ali, R. Dual modularity optimization for detecting overlapping communities in bipartite networks. Knowl Inf Syst 40, 455–488 (2014). https://doi.org/10.1007/s10115-013-0644-8

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