IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v389y2010i14p2849-2857.html
   My bibliography  Save this article

Detecting community structure in complex networks via node similarity

Author

Listed:
  • Pan, Ying
  • Li, De-Hua
  • Liu, Jian-Guo
  • Liang, Jing-Zhang

Abstract

The detection of the community structure in networks is beneficial to understand the network structure and to analyze the network properties. Based on node similarity, a fast and efficient method for detecting community structure is proposed, which discovers the community structure by iteratively incorporating the community containing a node with the communities that contain the nodes with maximum similarity to this node to form a new community. The presented method has low computational complexity because of requiring only the local information of the network, and it does not need any prior knowledge about the communities and its detection results are robust on the selection of the initial node. Some real-world and computer-generated networks are used to evaluate the performance of the presented method. The simulation results demonstrate that this method is efficient to detect community structure in complex networks, and the ZLZ metrics used in the proposed method is the most suitable one among local indices in community detection.

Suggested Citation

  • Pan, Ying & Li, De-Hua & Liu, Jian-Guo & Liang, Jing-Zhang, 2010. "Detecting community structure in complex networks via node similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2849-2857.
  • Handle: RePEc:eee:phsmap:v:389:y:2010:i:14:p:2849-2857
    DOI: 10.1016/j.physa.2010.03.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437110002050
    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.2010.03.006?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. Liu, Jian-Guo & Zhou, Tao & Che, Hong-An & Wang, Bing-Hong & Zhang, Yi-Cheng, 2010. "Effects of high-order correlations on personalized recommendations for bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 881-886.
    2. Tao Zhou & Linyuan Lü & Yi-Cheng Zhang, 2009. "Predicting missing links via local information," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(4), pages 623-630, October.
    3. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    4. Jian-Guo Liu & Bing-Hong Wang & Qiang Guo, 2009. "Improved Collaborative Filtering Algorithm Via Information Transformation," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 20(02), pages 285-293.
    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, Wenjun & Liu, Dong & Liu, Xiao & Pan, Lin, 2013. "Fuzzy overlapping community detection based on local random walk and multidimensional scaling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6578-6586.
    2. Yan, Chao & Chang, Zhenhai, 2020. "Modularized convex nonnegative matrix factorization for community detection in signed and unsigned networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    3. Shang, Ronghua & Bai, Jing & Jiao, Licheng & Jin, Chao, 2013. "Community detection based on modularity and an improved genetic algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1215-1231.
    4. Shang, Ronghua & Luo, Shuang & Zhang, Weitong & Stolkin, Rustam & Jiao, Licheng, 2016. "A multiobjective evolutionary algorithm to find community structures based on affinity propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 203-227.
    5. 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).
    6. Yang, Kai & Guo, Qiang & Liu, Jian-Guo, 2018. "Community detection via measuring the strength between nodes for dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 256-264.
    7. Aron Culotta & Jennifer Cutler, 2016. "Mining Brand Perceptions from Twitter Social Networks," Marketing Science, INFORMS, vol. 35(3), pages 343-362, May.
    8. Dabaghi Zarandi, Fataneh & Kuchaki Rafsanjani, Marjan, 2018. "Community detection in complex networks using structural similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 882-891.
    9. Lü, Linyuan & Zhou, Tao, 2011. "Link prediction in complex networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1150-1170.
    10. Gao, Jian & Zhou, Tao, 2017. "Evaluating user reputation in online rating systems via an iterative group-based ranking method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 546-560.
    11. Liu, Xu & Forrest, Jeffrey Yi-Lin & Luo, Qiang & Yi, Dong-Yun, 2012. "Detecting community structure using biased random merging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1797-1810.
    12. Chen, Ling-Jiao & Zhang, Zi-Ke & Liu, Jin-Hu & Gao, Jian & Zhou, Tao, 2017. "A vertex similarity index for better personalized recommendation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 607-615.
    13. Zhao, Zi-Juan & Guo, Qiang & Yu, Kai & Liu, Jian-Guo, 2020. "Identifying influential nodes for the networks with community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    14. Gong, Maoguo & Liu, Jie & Ma, Lijia & Cai, Qing & Jiao, Licheng, 2014. "Novel heuristic density-based method for community detection in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 71-84.
    15. Ai, Jun & Cai, Yifang & Su, Zhan & Zhang, Kuan & Peng, Dunlu & Chen, Qingkui, 2022. "Predicting user-item links in recommender systems based on similarity-network resource allocation," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    16. Zhang, Yuan & Li, Lu & Zhang, Wenbo & Cheng, Qixiu, 2022. "GATC and DeepCut: Deep spatiotemporal feature extraction and clustering for large-scale transportation network partition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    17. Zhou, Kuang & Martin, Arnaud & Pan, Quan, 2015. "A similarity-based community detection method with multiple prototype representation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 519-531.
    18. Gong, Maoguo & Ma, Lijia & Zhang, Qingfu & Jiao, Licheng, 2012. "Community detection in networks by using multiobjective evolutionary algorithm with decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 4050-4060.
    19. Zhu, Junfang & Ren, Xuezao & Ma, Peijie & Gao, Kun & Wang, Bing-Hong & Zhou, Tao, 2022. "Detecting network communities via greedy expanding based on local superiority index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    20. Sun, Hong-liang & Ch’ng, Eugene & Yong, Xi & Garibaldi, Jonathan M. & See, Simon & Chen, Duan-bing, 2018. "A fast community detection method in bipartite networks by distance dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 108-120.
    21. Xiang, Ju & Hu, Tao & Zhang, Yan & Hu, Ke & Li, Jian-Ming & Xu, Xiao-Ke & Liu, Cui-Cui & Chen, Shi, 2016. "Local modularity for community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 451-459.
    22. Chae, Bongsug (Kevin), 2019. "A General framework for studying the evolution of the digital innovation ecosystem: The case of big data," International Journal of Information Management, Elsevier, vol. 45(C), pages 83-94.
    23. Wu, Tao & Chen, Leiting & Zhong, Linfeng & Xian, Xingping, 2017. "Predicting the evolution of complex networks via similarity dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 662-672.

    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. Yu, Fei & Zeng, An & Gillard, Sébastien & Medo, Matúš, 2016. "Network-based recommendation algorithms: A review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 192-208.
    2. Liu, Ji & Deng, Guishi, 2009. "Link prediction in a user–object network based on time-weighted resource allocation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3643-3650.
    3. Emerson, Isaac Arnold & Amala, Arumugam, 2017. "Protein contact maps: A binary depiction of protein 3D structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 782-791.
    4. Faedo, Nicolás & García-Violini, Demián & Ringwood, John V., 2021. "Controlling synchronization in a complex network of nonlinear oscillators via feedback linearisation and H∞-control," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    5. 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.
    6. Ruiz Vargas, E. & Mitchell, D.G.V. & Greening, S.G. & Wahl, L.M., 2014. "Topology of whole-brain functional MRI networks: Improving the truncated scale-free model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 151-158.
    7. Igor Belykh & Mateusz Bocian & Alan R. Champneys & Kevin Daley & Russell Jeter & John H. G. Macdonald & Allan McRobie, 2021. "Emergence of the London Millennium Bridge instability without synchronisation," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    8. Berahmand, Kamal & Bouyer, Asgarali & Samadi, Negin, 2018. "A new centrality measure based on the negative and positive effects of clustering coefficient for identifying influential spreaders in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 41-54.
    9. 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).
    10. Soh, Harold & Lim, Sonja & Zhang, Tianyou & Fu, Xiuju & Lee, Gary Kee Khoon & Hung, Terence Gih Guang & Di, Pan & Prakasam, Silvester & Wong, Limsoon, 2010. "Weighted complex network analysis of travel routes on the Singapore public transportation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5852-5863.
    11. Wang, Qingyun & Duan, Zhisheng & Chen, Guanrong & Feng, Zhaosheng, 2008. "Synchronization in a class of weighted complex networks with coupling delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5616-5622.
    12. Karimi, Fatemeh & Lotfi, Shahriar & Izadkhah, Habib, 2021. "Community-guided link prediction in multiplex networks," Journal of Informetrics, Elsevier, vol. 15(4).
    13. Park, Jinhee & Ahn, Hyeongjin & Kim, Dongjae & Park, Eunil, 2024. "GNN-IR: Examining graph neural networks for influencer recommendations in social media marketing," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    14. 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.
    15. Lin, Dan & Wu, Jiajing & Xuan, Qi & Tse, Chi K., 2022. "Ethereum transaction tracking: Inferring evolution of transaction networks via link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    16. De Montis, Andrea & Ganciu, Amedeo & Cabras, Matteo & Bardi, Antonietta & Mulas, Maurizio, 2019. "Comparative ecological network analysis: An application to Italy," Land Use Policy, Elsevier, vol. 81(C), pages 714-724.
    17. Chen, Ling-Jiao & Zhang, Zi-Ke & Liu, Jin-Hu & Gao, Jian & Zhou, Tao, 2017. "A vertex similarity index for better personalized recommendation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 607-615.
    18. He, He & Yang, Bo & Hu, Xiaoming, 2016. "Exploring community structure in networks by consensus dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 342-353.
    19. T. Botmart & N. Yotha & P. Niamsup & W. Weera, 2017. "Hybrid Adaptive Pinning Control for Function Projective Synchronization of Delayed Neural Networks with Mixed Uncertain Couplings," Complexity, Hindawi, vol. 2017, pages 1-18, August.
    20. Sgrignoli, P. & Agliari, E. & Burioni, R. & Schianchi, A., 2015. "Instability and network effects in innovative markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 108(C), pages 260-271.

    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:389:y:2010:i:14:p:2849-2857. 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.