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Multilink communities of multiplex networks

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  • Raul J Mondragon
  • Jacopo Iacovacci
  • Ginestra Bianconi

Abstract

Multiplex networks describe a large number of complex social, biological and transportation networks where a set of nodes is connected by links of different nature and connotation. Here we uncover the rich community structure of multiplex networks by associating a community to each multilink where the multilinks characterize the connections existing between any two nodes of the multiplex network. Our community detection method reveals the rich interplay between the mesoscale structure of the multiplex networks and their multiplexity. For instance some nodes can belong to many layers and few communities while others can belong to few layers but many communities. Moreover the multilink communities can be formed by a different number of relevant layers. These results point out that mesoscopically there can be large differences in the compressibility of multiplex networks.

Suggested Citation

  • Raul J Mondragon & Jacopo Iacovacci & Ginestra Bianconi, 2018. "Multilink communities of multiplex networks," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-15, March.
    • Handle: RePEc:plo:pone00:0193821
    DOI: 10.1371/journal.pone.0193821
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    Cited by:

    1. Baccini, Federica & Barabesi, Lucio & Baccini, Alberto & Khelfaoui, Mahdi & Gingras, Yves, 2022. "Similarity network fusion for scholarly journals," Journal of Informetrics, Elsevier, vol. 16(1).
    2. Marialisa Scatá & Barbara Attanasio & Aurelio La Corte, 2021. "Cognitive Profiling of Nodes in 6G through Multiplex Social Network and Evolutionary Collective Dynamics," Future Internet, MDPI, vol. 13(5), pages 1-17, May.
    3. Feng, Zhijun & Cai, Hechang & Chen, Zinan & Zhou, Wen, 2022. "Influence of an interurban innovation network on the innovation capacity of China: A multiplex network perspective," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    4. Dewan F. Wahid & Elkafi Hassini, 2022. "A Literature Review on Correlation Clustering: Cross-disciplinary Taxonomy with Bibliometric Analysis," SN Operations Research Forum, Springer, vol. 3(3), pages 1-42, September.
    5. Wang, Shuliang & Lv, Wenzhuo & Zhao, Longfeng & Nie, Sen & Stanley, H. Eugene, 2019. "Structural and functional robustness of networked critical infrastructure systems under different failure scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 476-487.

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