IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v388y2009i14p2975-2986.html
   My bibliography  Save this article

Extracting hierarchical organization of complex networks by dynamics towards synchronization

Author

Listed:
  • Wang, Xiao-Hua
  • Jiao, Li-Cheng
  • Wu, Jian-She

Abstract

Based on the dynamics towards synchronization in hierarchical networks, we present an efficient method for extracting hierarchical organization in complex network. In the synchronization process, hierarchical structures corresponding to well defined communities of nodes emerge in different time scales, ordered in a hierarchical way. Thus, a new strategy for quantifying the dissimilarity between a pair of nodes in networks is introduced according to their time scales of synchronization. Then, using such a dissimilarity measure in conjunction with a hierarchical clustering method, our extracting method is proposed. The performance of our approach is tested on a set of computer generated and real-world networks with known hierarchical organization. The results demonstrate that our method enables us to offer insight into the complex networks with a multi-scale description. In addition, using a criterion of modularity, the method can also accurately find community structures in complex networks.

Suggested Citation

  • Wang, Xiao-Hua & Jiao, Li-Cheng & Wu, Jian-She, 2009. "Extracting hierarchical organization of complex networks by dynamics towards synchronization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2975-2986.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:14:p:2975-2986
    DOI: 10.1016/j.physa.2009.03.044
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437109002556
    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.2009.03.044?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.

    Citations

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


    Cited by:

    1. 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.
    2. Henry Dorrian & Jon Borresen & Martyn Amos, 2013. "Community Structure and Multi-Modal Oscillations in Complex Networks," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-10, October.

    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:388:y:2009:i:14:p:2975-2986. 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.