IDEAS home Printed from
   My bibliography  Save this article

Using Social Network Analysis to Support Collective Decision-Making Process


  • Simon Buckingham Shum

    (The Open University, UK)

  • Lorella Cannavacciuolo

    (University of Naples Federico II, Italy)

  • Anna De Liddo

    (The Open University, UK)

  • Luca Iandoli

    (University of Naples Federico II, Italy)

  • Ivana Quinto

    (University of Naples Federico II, Italy)


Current traditional technologies, while enabling effective knowledge sharing and accumulation, seem to be less supportive of knowledge organization, use and consensus formation, as well as of collaborative decision making process. To address these limitations and thus to better foster collective decision-making around complex and controversial problems, a new family of tools is emerging able to support more structured knowledge representations known as collaborative argument mapping tools. This paper argues that online collaborative argumentation has the rather unique feature of combining knowledge organization with social mapping and that such a combination can provide interesting insights on the social processes activated within a collaborative decision making initiative. In particular, the authors investigate how Social Network Analysis can be used for the analysis of the collective argumentation process to study the structural properties of the concepts and social networks emerging from users’ interaction. Using Cohere, an online platform designed to support collaborative argumentation, some empirical findings obtained from two use cases are presented.

Suggested Citation

  • Simon Buckingham Shum & Lorella Cannavacciuolo & Anna De Liddo & Luca Iandoli & Ivana Quinto, 2011. "Using Social Network Analysis to Support Collective Decision-Making Process," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 3(2), pages 15-31, April.
  • Handle: RePEc:igg:jdsst0:v:3:y:2011:i:2:p:15-31

    Download full text from publisher

    File URL:
    Download Restriction: no


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

    Cited by:

    1. Nelson Baloian & Gustavo Zurita, 2016. "Achieving better usability of software supporting learning activities of large groups," Information Systems Frontiers, Springer, vol. 18(1), pages 125-144, February.
    2. Tavana, Madjid & Di Caprio, Debora, 2016. "Modeling synergies in multi-criteria supplier selection and order allocation: An application to commodity tradingAuthor-Name: Sodenkamp, Mariya A," European Journal of Operational Research, Elsevier, vol. 254(3), pages 859-874.

    More about this item


    Access and download statistics


    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:igg:jdsst0:v:3:y:2011:i:2:p:15-31. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Journal Editor). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.