IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v519y2019icp181-194.html
   My bibliography  Save this article

Community detection in complex networks using edge-deleting with restrictions

Author

Listed:
  • Chen, Xiangtao
  • Li, Juan

Abstract

Community detection is an important task with great practical significance for understanding the structure and function of complex networks in various fields. As the real world networks become larger and more complex, it is a challenge to achieve high quality of community partitioning. In order to identify community structure more effectively in complex networks, a new algorithm, which iteratively deletes edges with restrictions is proposed in this paper. The algorithm first makes use of the connection strength between vertices to divide the original network into some strongly connected communities with optimal modularity by the improved edge-deleting process, and finally reconnects the isolated vertices to initial communities for optimizing community structure. Experiments on the real-world and synthetic networks prove that the proposed algorithm achieves a competitive performance compared with other reference algorithms.

Suggested Citation

  • Chen, Xiangtao & Li, Juan, 2019. "Community detection in complex networks using edge-deleting with restrictions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 181-194.
    • Handle: RePEc:eee:phsmap:v:519:y:2019:i:c:p:181-194
    DOI: 10.1016/j.physa.2018.12.023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118315358
    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.2018.12.023?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. Eustace, Justine & Wang, Xingyuan & Cui, Yaozu, 2015. "Community detection using local neighborhood in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 665-677.
    2. 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.
    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. Xinyu Wang & Liang Zhao & Ning Zhang & Liu Feng & Haibo Lin, 2022. "Stability of China's Stock Market: Measure and Forecast by Ricci Curvature on Network," Papers 2204.06692, arXiv.org.
    2. Yanjie Xu & Tao Ren & Shixiang Sun, 2022. "Community Detection Based on Node Influence and Similarity of Nodes," Mathematics, MDPI, vol. 10(6), pages 1-15, March.
    3. Fei Ma & Huifeng Xue & Kum Fai Yuen & Qipeng Sun & Shumei Zhao & Yanxia Zhang & Kai Huang, 2020. "Assessing the Vulnerability of Logistics Service Supply Chain Based on Complex Network," Sustainability, MDPI, vol. 12(5), pages 1-18, March.
    4. Wang, Tao & Chen, Shanshan & Wang, Xiaoxia & Wang, Jinfang, 2020. "Label propagation algorithm based on node importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    5. Pierre Bertrand & Michel Broniatowski & Jean-François Marcotorchino, 2022. "Independence versus indetermination: basis of two canonical clustering criteria," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(4), pages 1069-1093, December.
    6. Lai, Xin & Bai, Shuliang & Lin, Yong, 2022. "Normalized discrete Ricci flow used in community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).

    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. 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.
    2. Zhang, Yun & Liu, Yongguo & Li, Jieting & Zhu, Jiajing & Yang, Changhong & Yang, Wen & Wen, Chuanbiao, 2020. "WOCDA: A whale optimization based community detection algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    3. Rezvanian, Alireza & Meybodi, Mohammad Reza, 2015. "Sampling social networks using shortest paths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 254-268.
    4. 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.
    5. Etienne Côme & Nicolas Jouvin & Pierre Latouche & Charles Bouveyron, 2021. "Hierarchical clustering with discrete latent variable models and the integrated classification likelihood," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(4), pages 957-986, December.
    6. Namtirtha, Amrita & Dutta, Animesh & Dutta, Biswanath, 2018. "Identifying influential spreaders in complex networks based on kshell hybrid method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 310-324.
    7. Wang, Zhixiao & Zhao, Ya & Xi, Jingke & Du, Changjiang, 2016. "Fast ranking influential nodes in complex networks using a k-shell iteration factor," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 171-181.
    8. Zareie, Ahmad & Sheikhahmadi, Amir, 2019. "EHC: Extended H-index Centrality measure for identification of users’ spreading influence in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 141-155.
    9. Hu, Fang & Liu, Jia & Li, Liuhuan & Liang, Jun, 2020. "Community detection in complex networks using Node2vec with spectral clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    10. Xu, Shuang & Wang, Pei, 2017. "Identifying important nodes by adaptive LeaderRank," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 654-664.
    11. Tasgin, Mursel & Bingol, Haluk O., 2018. "Community detection using preference networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 126-136.
    12. Rosenberg, Eric, 2018. "Generalized Hausdorff dimensions of a complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 1-17.
    13. Nan, Dong-Yang & Yu, Wei & Liu, Xiao & Zhang, Yun-Peng & Dai, Wei-Di, 2018. "A framework of community detection based on individual labels in attribute networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 523-536.
    14. Antiqueira, L. & Nunes, M.G.V. & Oliveira Jr., O.N. & F. Costa, L. da, 2007. "Strong correlations between text quality and complex networks features," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 811-820.
    15. Wang, Tao & Wang, Hongjue & Wang, Xiaoxia, 2015. "A novel cosine distance for detecting communities in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 21-35.
    16. Wang, Tao & Chen, Shanshan & Wang, Xiaoxia & Wang, Jinfang, 2020. "Label propagation algorithm based on node importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    17. 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).
    18. Su, Zhen & Liu, Fanzhen & Gao, Chao & Gao, Shupeng & Li, Xianghua, 2018. "Inferring infection rate based on observations in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 170-176.
    19. Šubelj, Lovro & Bajec, Marko, 2011. "Community structure of complex software systems: Analysis and applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2968-2975.
    20. Li, Xiaojia & Li, Menghui & Hu, Yanqing & Di, Zengru & Fan, Ying, 2010. "Detecting community structure from coherent oscillation of excitable systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 164-170.

    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:519:y:2019:i:c:p:181-194. 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.