IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0283857.html

Overlapping communities detection through weighted graph community games

Author

Listed:
  • Stefano Benati
  • Justo Puerto
  • Antonio M Rodríguez-Chía
  • Francisco Temprano

Abstract

We propose a new model to detect the overlapping communities of a network that is based on cooperative games and mathematical programming. More specifically, communities are defined as stable coalitions of a weighted graph community game and they are revealed as the optimal solution of a mixed-integer linear programming problem. Exact optimal solutions are obtained for small and medium sized instances and it is shown that they provide useful information about the network structure, improving on previous contributions. Next, a heuristic algorithm is developed to solve the largest instances and used to compare two variations of the objective function.

Suggested Citation

  • Stefano Benati & Justo Puerto & Antonio M Rodríguez-Chía & Francisco Temprano, 2023. "Overlapping communities detection through weighted graph community games," PLOS ONE, Public Library of Science, vol. 18(4), pages 1-35, April.
  • Handle: RePEc:plo:pone00:0283857
    DOI: 10.1371/journal.pone.0283857
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0283857
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0283857&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0283857?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Alejandro Caparrós & Eric Giraud-Héraud & Abdelhakim Hammoudi & Tarik Tazdaït, 2011. "Coalition Stability with Heterogeneous Agents," Economics Bulletin, AccessEcon, vol. 31(1), pages 286-296.
    2. Demange, Gabrielle, 1994. "Intermediate preferences and stable coalition structures," Journal of Mathematical Economics, Elsevier, vol. 23(1), pages 45-58, January.
    3. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
    4. Pablo M. Gleiser & Leon Danon, 2003. "Community Structure In Jazz," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 565-573.
    5. Zhang, Shihua & Wang, Rui-Sheng & Zhang, Xiang-Sun, 2007. "Identification of overlapping community structure in complex networks using fuzzy c-means clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 483-490.
    6. G. Agarwal & D. Kempe, 2008. "Modularity-maximizing graph communities via mathematical programming," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 66(3), pages 409-418, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Benati, Stefano & Puerto, Justo & Temprano, Francisco, 2026. "Modularity for hypergraph clustering: Methodologies and applications," Omega, Elsevier, vol. 138(C).
    2. Ailian Wang & Mingwu Li & Xuyang Gao & Bolin Li & Zhiqiang Su, 2025. "Overlapping community detection based on bridging structural features and fuzzy C-means," PLOS ONE, Public Library of Science, vol. 20(8), pages 1-20, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, X. & Murata, T., 2010. "Advanced modularity-specialized label propagation algorithm for detecting communities in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1493-1500.
    2. Sukeda, Issey & Miyauchi, Atsushi & Takeda, Akiko, 2023. "A study on modularity density maximization: Column generation acceleration and computational complexity analysis," European Journal of Operational Research, Elsevier, vol. 309(2), pages 516-528.
    3. Xiang-Sun Zhang & Zhenping Li & Rui-Sheng Wang & Yong Wang, 2012. "A combinatorial model and algorithm for globally searching community structure in complex networks," Journal of Combinatorial Optimization, Springer, vol. 23(4), pages 425-442, May.
    4. Bi, Yilin & Bian, Junhao & Wan, Shuyan & Wang, Shuaijia & Zhou, Tao, 2026. "Domain matters: Towards domain-informed evaluation for link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 693(C).
    5. Liu, Panfeng & Li, Longjie & Fang, Shiyu & Yao, Yukai, 2021. "Identifying influential nodes in social networks: A voting approach," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    6. Yazdanparast, Sakineh & Havens, Timothy C., 2017. "Modularity maximization using completely positive programming," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 20-32.
    7. Benati, Stefano & Puerto, Justo & Temprano, Francisco, 2026. "Modularity for hypergraph clustering: Methodologies and applications," Omega, Elsevier, vol. 138(C).
    8. Peng Wu & Li Pan, 2015. "Multi-Objective Community Detection Based on Memetic Algorithm," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-31, May.
    9. Zhou, Xu & Liu, Yanheng & Zhang, Jindong & Liu, Tuming & Zhang, Di, 2015. "An ant colony based algorithm for overlapping community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 289-301.
    10. Gao, Zi-Ni & Zhang, Hai-Feng & Ma, Chuang, 2026. "A Monte Carlo-enhanced approach for link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 695(C).
    11. Yin, Likang & Zheng, Haoyang & Bian, Tian & Deng, Yong, 2017. "An evidential link prediction method and link predictability based on Shannon entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 699-712.
    12. You, Tao & Cheng, Hui-Min & Ning, Yi-Zi & Shia, Ben-Chang & Zhang, Zhong-Yuan, 2016. "Community detection in complex networks using density-based clustering algorithm and manifold learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 221-230.
    13. Jianjun Cheng & Xing Su & Haijuan Yang & Longjie Li & Jingming Zhang & Shiyan Zhao & Xiaoyun Chen, 2019. "Neighbor Similarity Based Agglomerative Method for Community Detection in Networks," Complexity, Hindawi, vol. 2019, pages 1-16, May.
    14. Jin Wang & Bo Huang & Xuefeng Xia & Zhirong Sun, 2006. "Funneled Landscape Leads to Robustness of Cell Networks: Yeast Cell Cycle," PLOS Computational Biology, Public Library of Science, vol. 2(11), pages 1-10, November.
    15. Jing Wang & Jing Wang & Jingfeng Guo & Liya Wang & Chunying Zhang & Bin Liu, 2023. "Research Progress of Complex Network Modeling Methods Based on Uncertainty Theory," Mathematics, MDPI, vol. 11(5), pages 1-27, March.
    16. Ke Hu & Ju Xiang & Yun-Xia Yu & Liang Tang & Qin Xiang & Jian-Ming Li & Yong-Hong Tang & Yong-Jun Chen & Yan Zhang, 2020. "Significance-based multi-scale method for network community detection and its application in disease-gene prediction," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-24, March.
    17. Jean-Marc Bourgeon & Marie-Laure Breuillé, 2023. "Citizen preferences and the architecture of government," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 61(3), pages 537-585, October.
    18. Zhou, Wei-Xing & Jiang, Zhi-Qiang & Sornette, Didier, 2007. "Exploring self-similarity of complex cellular networks: The edge-covering method with simulated annealing and log-periodic sampling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 741-752.
    19. Zhang, Wen-Yao & Wei, Zong-Wen & Wang, Bing-Hong & Han, Xiao-Pu, 2016. "Measuring mixing patterns in complex networks by Spearman rank correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 440-450.
    20. Alejandro Caparrós & Michael Finus, 2020. "Public good agreements under the weakest‐link technology," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 22(3), pages 555-582, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0283857. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.