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20 years of network community detection

Nature Physics volume 18, pages 848–850 (2022)Cite this article

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A fundamental technical challenge in the analysis of network data is the automated discovery of communities — groups of nodes that are strongly connected or that share similar features or roles. In this Comment we review progress in the field over the past 20 years.

Networks feature in many aspects of our lives, ranging from social networks of personal relationships, both on- and offline, biological networks of interactions between genes, metabolites and neurons, to technological networks such as the Internet, infrastructure and transportation networks. The modern science of networks investigates the structure and function of networks such as those composed of nodes representing the elementary units of the system and the links or edges that connect them1.

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Fig. 1: Community structure of a social network.

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Author information

Authors and Affiliations

  1. Indiana University Network Science Institute (IUNI), Bloomington, IN, USA

    Santo Fortunato

  2. Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA

    Santo Fortunato

  3. Department of Physics and Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI, USA

    Mark E. J. Newman

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  1. Santo Fortunato
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  2. Mark E. J. Newman
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Correspondence to Santo Fortunato.

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Fortunato, S., Newman, M.E.J. 20 years of network community detection. Nat. Phys. 18, 848–850 (2022). https://doi.org/10.1038/s41567-022-01716-7

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  • DOI: https://doi.org/10.1038/s41567-022-01716-7

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