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Force-directed algorithms as a tool to support community detection

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Abstract

Force-directed algorithms are a class of methods widely used to solve problems modeled via physics laws and resolved by particle simulation. Visualization of general graphs is one of the research fields which uses such algorithms and provides a vast knowledge about their benefits and challenges. Taking advantage of the knowledge provided by graph visualization theory, some authors have adopted force-directed algorithms as a tool to deal with the community detection problem. However, researches in that direction seem to be neglected by the literature of complex network. This paper explores the use of force-directed algorithms as a tool to solve the community detection problem. We revisit the works proposed in this area and point out the similarities, but mainly highlight the particularities of such a problem concerning the draw of a general graph. This literature review aims to organize the knowledge about the subject and highlight the state-of-the-art. To conduct our review, we followed a research protocol inspired by systematic review guidelines. Our review exposes that many works have chosen models that are not ideal for dealing with the community detection problem. Furthermore, we also highlight the most appropriate force-directed models for community detection.

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Notes

  1. Code available in https://code.google.com/archive/p/linloglayout.

  2. Figure 9b was made from the code available by Lim et al. at https://github.com/kaist-dmlab/BlackHole.

  3. The cycle is one iteration of the algorithm used to changes the vertex position according to the force system acting on them.

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Acknowledgements

This work was supported by the São Paulo Research Foundation (FAPESP), Proc. 2015/50122-0, 2016/23642-6, 2016/23698-1, 2016/16291-2, 2017/05831-9, 2019/26283-5, and 2019/00157-3; and the National Council for Scientific and Technological Development (CNPq), Proc. 434886/2018-1 and 313426/2018-0.

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Authors and Affiliations

  1. Federal University of São Paulo, São José dos Campos, SP, Brazil

    Alessandra M. M. M. Gouvêa, Tiago S. da Silva, Elbert E. N. Macau & Marcos G. Quiles

  2. National Institute for Space Research, São José dos Campos, SP, Brazil

    Elbert E. N. Macau

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  1. Alessandra M. M. M. Gouvêa
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  2. Tiago S. da Silva
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  3. Elbert E. N. Macau
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Contributions

A.M.M.M.G. was responsible for executing the review process, i.e., applying the search string on the database, merging the records, and selecting the records according to inclusion and exclusion criteria. T.S.S. focused on guaranteed the correct use of the guidelines on conducting systematic literature reviews, validating the decisions made during the review process. E.E.N.M. supported the correct use of interdisciplinary concepts. M.G.Q. supervised the inclusion and exclusion criteria and guarantee the quality of selected records. All authors contributed to the writing and reviewing of the manuscript.

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Correspondence to Alessandra M. M. M. Gouvêa.

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Gouvêa, A.M.M.M., da Silva, T.S., Macau, E.E.N. et al. Force-directed algorithms as a tool to support community detection. Eur. Phys. J. Spec. Top. 230, 2745–2763 (2021). https://doi.org/10.1140/epjs/s11734-021-00167-0

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