IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v534y2019ics0378437119312026.html
   My bibliography  Save this article

Community detection with the Label Propagation Algorithm: A survey

Author

Listed:
  • Garza, Sara E.
  • Schaeffer, Satu Elisa

Abstract

Community detection aims at discovering the structure, behavior, dynamics, and organization of a complex network by finding cohesive groups where nodes (entities) are, in some sense, more similar within the group and groups are in some fashion separated from the other groups. The Label Propagation Algorithm (LPA), which mimics epidemic contagion by spreading labels, is a popular algorithm for this task. Its variants (enhancements, extensions, combinations) seek to improve or to adapt it while preserving the advantages of the original formulation. This survey gathers, classifies, and summarizes LPA-related advances from 2007 to mid 2019. We also experiment with combinations of numerous LPA “building blocks” on two types of small synthetic networks; essentially all of the 13,834 resulting LPA variants have their niche in terms of either higher solution quality or lower computational load with acceptable quality, but none is universally superior.

Suggested Citation

  • Garza, Sara E. & Schaeffer, Satu Elisa, 2019. "Community detection with the Label Propagation Algorithm: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    • Handle: RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119312026
    DOI: 10.1016/j.physa.2019.122058
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119312026
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.122058?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Michael T. SCHAUB & Jean-Charles DELVENNE, 2017. "The many facets of community detection in complex networks," LIDAM Reprints CORE 2890, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Wu, Tao & Chen, Leiting & Zhong, Linfeng & Xian, Xingping, 2017. "Enhanced collective influence: A paradigm to optimize network disruption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 43-52.
    3. Ding, Jiajun & He, Xiongxiong & Yuan, Junqing & Chen, Yan & Jiang, Bo, 2018. "Community detection by propagating the label of center," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 675-686.
    4. Huang, Jianbin & Sun, Heli & Han, Jiawei & Feng, Boqin, 2011. "Density-based shrinkage for revealing hierarchical and overlapping community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2160-2171.
    5. Wu, Tao & Guo, Yuxiao & Chen, Leiting & Liu, Yanbing, 2016. "Integrated structure investigation in complex networks by label propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 68-80.
    6. Duan-Bing Chen & Hui Gao & Linyuan Lü & Tao Zhou, 2013. "Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-10, October.
    7. Sun, Heli & Liu, Jiao & Huang, Jianbin & Wang, Guangtao & Yang, Zhou & Song, Qinbao & Jia, Xiaolin, 2015. "CenLP: A centrality-based label propagation algorithm for community detection in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 767-780.
    8. 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.
    9. Shang, Ronghua & Luo, Shuang & Li, Yangyang & Jiao, Licheng & Stolkin, Rustam, 2015. "Large-scale community detection based on node membership grade and sub-communities integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 279-294.
    10. Pagani, Giuliano Andrea & Aiello, Marco, 2013. "The Power Grid as a complex network: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(11), pages 2688-2700.
    11. Peng, Hao & Zhao, Dandan & Li, Lin & Lu, Jianfeng & Han, Jianmin & Wu, Songyang, 2016. "An improved label propagation algorithm using average node energy in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 98-104.
    12. L. Šubelj & M. Bajec, 2011. "Robust network community detection using balanced propagation," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 81(3), pages 353-362, June.
    13. Deng, Zheng-Hong & Qiao, Hong-Hai & Song, Qun & Gao, Li, 2019. "A complex network community detection algorithm based on label propagation and fuzzy C-means," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 217-226.
    14. Yuxin Zhao & Shenghong Li & Shilin Wang, 2014. "Agglomerative Clustering Based On Label Propagation For Detecting Overlapping And Hierarchical Communities In Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(06), pages 1-22.
    15. Lou, Hao & Li, Shenghong & Zhao, Yuxin, 2013. "Detecting community structure using label propagation with weighted coherent neighborhood propinquity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(14), pages 3095-3105.
    16. Badie, Reza & Aleahmad, Abolfazl & Asadpour, Masoud & Rahgozar, Maseud, 2013. "An efficient agent-based algorithm for overlapping community detection using nodes’ closeness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5231-5247.
    17. Lin, Zhen & Zheng, Xiaolin & Xin, Nan & Chen, Deren, 2014. "CK-LPA: Efficient community detection algorithm based on label propagation with community kernel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 386-399.
    18. Li, Qian & Zhou, Tao & Lü, Linyuan & Chen, Duanbing, 2014. "Identifying influential spreaders by weighted LeaderRank," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 47-55.
    19. Zhang, Weitong & Zhang, Rui & Shang, Ronghua & Jiao, Licheng, 2018. "Weighted compactness function based label propagation algorithm for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 767-780.
    20. Dongxiao He & Jie Liu & Bo Yang & Yuxiao Huang & Dayou Liu & Di Jin, 2012. "An Ant-Based Algorithm With Local Optimization For Community Detection In Large-Scale Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(08), pages 1-26.
    21. Chen, Naiyue & Liu, Yun & Chen, Haiqiang & Cheng, Junjun, 2017. "Detecting communities in social networks using label propagation with information entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 788-798.
    22. Andrea Lancichinetti & Filippo Radicchi & José J Ramasco & Santo Fortunato, 2011. "Finding Statistically Significant Communities in Networks," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-18, April.
    23. Šubelj, Lovro & Bajec, Marko, 2014. "Group detection in complex networks: An algorithm and comparison of the state of the art," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 144-156.
    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. Wang, Benyu & Gu, Yijun & Zheng, Diwen, 2022. "Community detection in error-prone environments based on particle cooperation and competition with distance dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    2. Yanmei Hu & Bo Yang & Bin Duo & Xing Zhu, 2022. "Exhaustive Exploitation of Local Seeding Algorithms for Community Detection in a Unified Manner," Mathematics, MDPI, vol. 10(15), pages 1-30, August.
    3. Hosseini-Pozveh, Maryam & Ghorbanian, Maedeh & Tabaiyan, Maryam, 2022. "A label propagation-based method for community detection in directed signed social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    4. Jing Yang & Jun Wang & Mengyang Gao, 2023. "Community Evolution Analysis Driven by Tag Events: The Special Perspective of New Tags," Mathematics, MDPI, vol. 11(6), pages 1-18, March.

    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. Laassem, Brahim & Idarrou, Ali & Boujlaleb, Loubna & Iggane, M’bark, 2022. "Label propagation algorithm for community detection based on Coulomb’s law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    2. Ma, Tinghuai & Yue, Mingliang & Qu, Jingjing & Tian, Yuan & Al-Dhelaan, Abdullah & Al-Rodhaan, Mznah, 2018. "PSPLPA: Probability and similarity based parallel label propagation algorithm on spark," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 366-378.
    3. Hosseini-Pozveh, Maryam & Ghorbanian, Maedeh & Tabaiyan, Maryam, 2022. "A label propagation-based method for community detection in directed signed social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    4. Shang, Ronghua & Zhang, Weitong & Jiao, Licheng & Stolkin, Rustam & Xue, Yu, 2017. "A community integration strategy based on an improved modularity density increment for large-scale networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 471-485.
    5. Lovro Šubelj & Nees Jan van Eck & Ludo Waltman, 2016. "Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-23, April.
    6. Qiao, Honghai & Deng, Zhenghong & Li, Huijia & Hu, Jun & Song, Qun & Xia, Chengyi, 2021. "Complex networks from time series data allow an efficient historical stage division of urban air quality information," Applied Mathematics and Computation, Elsevier, vol. 410(C).
    7. Fang, Wenyi & Wang, Xin & Liu, Longzhao & Wu, Zhaole & Tang, Shaoting & Zheng, Zhiming, 2022. "Community detection through vector-label propagation algorithms," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    8. Wu, Tao & Chen, Leiting & Zhong, Linfeng & Xian, Xingping, 2017. "Enhanced collective influence: A paradigm to optimize network disruption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 43-52.
    9. Li, Wei & Huang, Ce & Wang, Miao & Chen, Xi, 2017. "Stepping community detection algorithm based on label propagation and similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 145-155.
    10. Zhang, Jun-li & Fu, Yan-jun & Cheng, Lan & Yang, Yun-yun, 2021. "Identifying multiple influential spreaders based on maximum connected component decomposition method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    11. Luo, Mengdi & Xu, Ying, 2022. "Community detection via network node vector label propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    12. Dušan Džamić & Daniel Aloise & Nenad Mladenović, 2019. "Ascent–descent variable neighborhood decomposition search for community detection by modularity maximization," Annals of Operations Research, Springer, vol. 272(1), pages 273-287, January.
    13. Tasgin, Mursel & Bingol, Haluk O., 2019. "Community detection using boundary nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 315-324.
    14. Lin, Zhen & Zheng, Xiaolin & Xin, Nan & Chen, Deren, 2014. "CK-LPA: Efficient community detection algorithm based on label propagation with community kernel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 386-399.
    15. Liu, Qiang & Zhu, Yu-Xiao & Jia, Yan & Deng, Lu & Zhou, Bin & Zhu, Jun-Xing & Zou, Peng, 2018. "Leveraging local h-index to identify and rank influential spreaders in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 379-391.
    16. Zareie, Ahmad & Sheikhahmadi, Amir & Fatemi, Adel, 2017. "Influential nodes ranking in complex networks: An entropy-based approach," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 485-494.
    17. Aghaalizadeh, Saeid & Afshord, Saeid Taghavi & Bouyer, Asgarali & Anari, Babak, 2021. "A three-stage algorithm for local community detection based on the high node importance ranking in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    18. Wu, Jianshe & Zhang, Long & Li, Yong & Jiao, Yang, 2016. "Partition signed social networks via clustering dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 568-582.
    19. Gregory, Steve, 2012. "Ordered community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2752-2763.
    20. Tselykh, Alexander & Vasilev, Vladislav & Tselykh, Larisa, 2019. "Clustering method based on the elastic energy functional of directed signed weighted graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 392-407.

    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:eee:phsmap:v:534:y:2019:i:c:s0378437119312026. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.