IDEAS home Printed from https://ideas.repec.org/a/ids/ijitma/v8y2009i1p33-49.html
   My bibliography  Save this article

The small-world and scale-free structure of an internet technological community

Author

Listed:
  • Jie Yan
  • Dimitris Assimakopoulos

Abstract

Two network topology models, 'small-world' and 'scale-free' networks, have been recently introduced by physicists and mathematicians, generating a growing interest from the natural and social scientists interested in the dynamics of networks and related communities. In this paper, we analyse the structure of the questioning and replying network in a very large internet technical community, China Software Development Net (CSDN). CSDN is the biggest Chinese language software technical forum, with over one million registered members by early 2006. Our findings indicate that the CSDN network presents both small-world and scale-free properties. The technology and knowledge management implications for this network structure are discussed with respect to the technical knowledge and innovation diffusion in large technological communities.

Suggested Citation

  • Jie Yan & Dimitris Assimakopoulos, 2009. "The small-world and scale-free structure of an internet technological community," International Journal of Information Technology and Management, Inderscience Enterprises Ltd, vol. 8(1), pages 33-49.
    • Handle: RePEc:ids:ijitma:v:8:y:2009:i:1:p:33-49
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=22269
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Lian, Ying & Dong, Xuefan & Liu, Yijun, 2017. "Topological evolution of the internet public opinion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 567-578.
    2. Rong, Rong & Houser, Daniel, 2015. "Growing stars: A laboratory analysis of network formation," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 380-394.
    3. Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2018. "Experts in Knowledge Networks: Central Positioning and Intelligent Selections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 890-905.
    4. Dong, Xuefan & Liu, Yijung & Wu, Chao & Lian, Ying, 2019. "The topology of scale-free networks with an S-shaped nonlinear growth characteristic," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 137-148.

    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:ids:ijitma:v:8:y:2009:i:1:p:33-49. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=18 .

    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.