IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v436y2015icp665-677.html
   My bibliography  Save this article

Community detection using local neighborhood in complex networks

Author

Listed:
  • Eustace, Justine
  • Wang, Xingyuan
  • Cui, Yaozu

Abstract

It is common to characterize community structure in complex networks using local neighborhood. Existing related methods fail to estimate the accurate number of nodes present in each community in the network. In this paper a community detection algorithm using local community neighborhood ratio function is proposed. The proposed algorithm predicts vertex association to a specific community using visited node overlapped neighbors. In the beginning, the algorithm detects local communities; then through iterations and local neighborhood ratio function, final communities are detected by merging close related local communities. Analysis of simulation results on real and artificial networks shows the proposed algorithm detects well defined communities in both networks by wide margin.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:436:y:2015:i:c:p:665-677
    DOI: 10.1016/j.physa.2015.05.044
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437115004598
    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.2015.05.044?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. Gergely Palla & Imre Derényi & Illés Farkas & Tamás Vicsek, 2005. "Uncovering the overlapping community structure of complex networks in nature and society," Nature, Nature, vol. 435(7043), pages 814-818, June.
    2. Shen, Huawei & Cheng, Xueqi & Cai, Kai & Hu, Mao-Bin, 2009. "Detect overlapping and hierarchical community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1706-1712.
    3. Jianbin Huang & Heli Sun & Yaguang Liu & Qinbao Song & Tim Weninger, 2011. "Towards Online Multiresolution Community Detection in Large-Scale Networks," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-11, August.
    4. 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.
    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. 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. 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).
    3. 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.
    4. 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.
    5. Zhu, Jiajing & Liu, Yongguo & Zhang, Yun & Liu, Xiaofeng & Xiao, Yonghua & Wang, Shidong & Wu, Xindong, 2017. "Exploring anti-community structure in networks with application to incompatibility of traditional Chinese medicine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 31-43.
    6. Zhang, Xiaolei & Ren, Yibin & Huang, Baoxiang & Han, Yong, 2018. "Analysis of time-varying characteristics of bus weighted complex network in Qingdao based on boarding passenger volume," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 376-394.
    7. Yang, Jin-Xuan & Zhang, Xiao-Dong, 2017. "Finding overlapping communities using seed set," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 96-106.
    8. 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.
    9. Wang, Tao & Yin, Liyan & Wang, Xiaoxia, 2018. "A community detection method based on local similarity and degree clustering information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1344-1354.
    10. 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.
    11. 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.
    12. 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).
    13. 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.
    14. 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.

    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, Zhihao & Lin, Youfang & Wan, Huaiyu & Tian, Shengfeng & Hu, Keyun, 2012. "Efficient overlapping community detection in huge real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2475-2490.
    2. Zhou, Xu & Liu, Yanheng & Wang, Jian & Li, Chun, 2017. "A density based link clustering algorithm for overlapping community detection in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 65-78.
    3. Wu, Jianshe & Wang, Xiaohua & Jiao, Licheng, 2012. "Synchronization on overlapping community network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 508-514.
    4. 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.
    5. Fu, Xianghua & Liu, Liandong & Wang, Chao, 2013. "Detection of community overlap according to belief propagation and conflict," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 941-952.
    6. Hao Xu & Yuan Ran & Junqian Xing & Li Tao, 2023. "An Influence-Based Label Propagation Algorithm for Overlapping Community Detection," Mathematics, MDPI, vol. 11(9), pages 1-17, May.
    7. Xiaofeng Wang & Gongshen Liu & Jianhua Li & Jan P Nees, 2017. "Locating Structural Centers: A Density-Based Clustering Method for Community Detection," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-23, January.
    8. 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.
    9. Tzai-Hung Wen & Wei Chien Benny Chin, 2015. "Incorporation of Spatial Interactions in Location Networks to Identify Critical Geo-Referenced Routes for Assessing Disease Control Measures on a Large-Scale Campus," IJERPH, MDPI, vol. 12(4), pages 1-15, April.
    10. Nicolò Pecora & Pablo Rovira Kaltwasser & Alessandro Spelta, 2016. "Discovering SIFIs in Interbank Communities," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-17, December.
    11. Cui, Yaozu & Wang, Xingyuan, 2016. "Detecting one-mode communities in bipartite networks by bipartite clustering triangular," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 307-315.
    12. Gui, Chun & Zhang, Ruisheng & Hu, Rongjing & Huang, Guoming & Wei, Jiaxuan, 2018. "Overlapping communities detection based on spectral analysis of line graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 498(C), pages 50-65.
    13. Ren, Fu-Xin & Shen, Hua-Wei & Cheng, Xue-Qi, 2012. "Modeling the clustering in citation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3533-3539.
    14. Huang, Zhenhua & Wu, Junxian & Zhu, Wentao & Wang, Zhenyu & Mehrotra, Sharad & Zhao, Yangyang, 2021. "Visualizing complex networks by leveraging community structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    15. 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.
    16. 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.
    17. Mu, Caihong & Liu, Yong & Liu, Yi & Wu, Jianshe & Jiao, Licheng, 2014. "Two-stage algorithm using influence coefficient for detecting the hierarchical, non-overlapping and overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 47-61.
    18. Zhang, Weitong & Zhang, Rui & Shang, Ronghua & Li, Juanfei & Jiao, Licheng, 2019. "Application of natural computation inspired method in community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 130-150.
    19. 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.
    20. Xiao‐Bing Hu & Hang Li & XiaoMei Guo & Pieter H. A. J. M. van Gelder & Peijun Shi, 2019. "Spatial Vulnerability of Network Systems under Spatially Local Hazards," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 162-179, January.

    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:436:y:2015:i:c:p:665-677. 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.