IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v358y2005i2p593-604.html
   My bibliography  Save this article

Detection of community structures in networks via global optimization

Author

Listed:
  • Medus, A.
  • Acuña, G.
  • Dorso, C.O.

Abstract

We present an analysis of communality structure in networks based on the application of simulated annealing techniques. In this case we use as “cost function” the already introduced modularity Q (1), which is based on the relative number of links within a commune against the number of links that would correspond in case the links were distributed randomly. We compare the results of our approach against other methodologies based on betweenness analysis and show that in all cases a better community structure can be attained.

Suggested Citation

  • Medus, A. & Acuña, G. & Dorso, C.O., 2005. "Detection of community structures in networks via global optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 358(2), pages 593-604.
  • Handle: RePEc:eee:phsmap:v:358:y:2005:i:2:p:593-604
    DOI: 10.1016/j.physa.2005.04.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437105003973
    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.2005.04.022?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.

    Citations

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


    Cited by:

    1. 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.
    2. 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.
    3. Xiang, Ju & Tang, Yan-Ni & Gao, Yuan-Yuan & Zhang, Yan & Deng, Ke & Xu, Xiao-Ke & Hu, Ke, 2015. "Multi-resolution community detection based on generalized self-loop rescaling strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 127-139.
    4. Li, Yafang & Jia, Caiyan & Yu, Jian, 2015. "A parameter-free community detection method based on centrality and dispersion of nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 321-334.
    5. Ma, Xiaoke & Gao, Lin & Yong, Xuerong & Fu, Lidong, 2010. "Semi-supervised clustering algorithm for community structure detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 187-197.
    6. Li, Zhangtao & Liu, Jing, 2016. "A multi-agent genetic algorithm for community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 336-347.
    7. Atsushi Miyauchi & Yasushi Kawase, 2016. "Z-Score-Based Modularity for Community Detection in Networks," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-17, January.
    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.

    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:358:y:2005:i:2:p:593-604. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.