IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v61y2008i3p371-376.html
   My bibliography  Save this article

Dynamics of opinion formation in hierarchical social networks: Network structure and initial bias

Author

Listed:
  • P. P. Li
  • P. M. Hui

Abstract

The dynamics of opinion formation based on a majority rule model is studied in a network with the social hierarchical structure as one of its limits. The exit probability is found to change sensitively with the number of nodes in the system, but not with the parameter of homophyly characterizing the network structure. The consensus time is found to be a result of non-trivial interplay between the network structure characterized by the parameter of homophyly and the initial bias in opinion. For unbiased initial opinion, a common consensus is easier to be reached in a random network than a highly structured hierarchical network and it follows the behavior of the length of shortest paths. For biased initial opinion, a common consensus is easier to be reached in a hierarchical network, as the local majority opinion of the groups may take on the biased opinions and hence be the same. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2008

Suggested Citation

  • P. P. Li & P. M. Hui, 2008. "Dynamics of opinion formation in hierarchical social networks: Network structure and initial bias," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 61(3), pages 371-376, February.
    • Handle: RePEc:spr:eurphb:v:61:y:2008:i:3:p:371-376
    DOI: 10.1140/epjb/e2008-00082-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1140/epjb/e2008-00082-4
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1140/epjb/e2008-00082-4?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. Shen, Han & Tu, Lilan & Wang, Xianjia, 2024. "The influence of emotional tendency on the dissemination and evolution of opinions in two-layer social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    2. Małgorzata J Krawczyk & Krzysztof Kułakowski & Janusz A Hołyst, 2018. "Hierarchical partitions of social networks between rivaling leaders," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-13, March.

    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:spr:eurphb:v:61:y:2008:i:3:p:371-376. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.