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Modularity and projection of bipartite networks

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  • Arthur, Rudy

Abstract

This paper investigates community detection by modularity maximisation on bipartite networks. In particular we are interested in how the operation of projection, using one node set of the bipartite network to infer connections between nodes in the other set, interacts with community detection. We first define a notion of modularity appropriate for a projected bipartite network and outline an algorithm for maximising it in order to partition the network. Using both real and synthetic networks we compare the communities found by five different algorithms, where each algorithm maximises a different modularity function and sees different aspects of the bipartite structure. Based on these results we suggest a simple ‘rule of thumb’ for finding communities in bipartite networks.

Suggested Citation

  • Arthur, Rudy, 2020. "Modularity and projection of bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    • Handle: RePEc:eee:phsmap:v:549:y:2020:i:c:s0378437120301151
    DOI: 10.1016/j.physa.2020.124341
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    References listed on IDEAS

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    1. Gergely Palla & Imre Derényi & Illés Farkas & Tamás Vicsek, 2005. "Uncovering the overlapping community structure of complex networks in nature and society," Nature, Nature, vol. 435(7043), pages 814-818, June.
    2. Nacher, J.C. & Akutsu, T., 2011. "On the degree distribution of projected networks mapped from bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4636-4651.
    3. Mukherjee, Animesh & Choudhury, Monojit & Ganguly, Niloy, 2011. "Understanding how both the partitions of a bipartite network affect its one-mode projection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3602-3607.
    4. Li, Yongjun & You, Chun, 2013. "What is the difference of research collaboration network under different projections: Topological measurement and analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(15), pages 3248-3259.
    5. Zhou, Cangqi & Feng, Liang & Zhao, Qianchuan, 2018. "A novel community detection method in bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1679-1693.
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    Cited by:

    1. Arthur, Rudy, 2023. "Discovering block structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 613(C).
    2. Neelu Chaudhary & Hardeo Kumar Thakur & Rinky Dwivedi, 2022. "An ensemble model to optimize modularity in dynamic bipartite networks," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2248-2260, October.

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