Analyzing Social Roles Based on a Hierarchical Model and Data Mining for Collective Decision-Making Support

Bo Wu, Xiaokang Zhou, Qun Jin, Fuhua Lin, Henry Leung

    Research output: Contribution to journalArticle

    5 Citations (Scopus)


    With the popularity of social networking services (SNSs) and the increase of users, individuals' social roles in a social network have become more and more important in terms of the recommendation of personalized services and the collective decision-making process. Usually, in an SNS system, active users may not represent the major opinions among the whole users, and most of the users' opinions may be multifarious. In this paper, we focus on analyzing and identifying users' dynamical social roles to facilitate the collective decision-making process. After introducing the social choice theory and an improved collective decision-making model, we present a three-layer model to analyze users' social roles in a hierarchical way and develop an integrated mechanism to utilize the identification of social roles to support the collective decision making. Based on a developed NetLogo-based tool, a case study for the course-offering determination with an application scenario is demonstrated to show the process of using users' social roles to support the collective decision making. The comparison experiment conducted between our method and the Delphi method shows the usefulness of our proposed method to help users achieve the decision consensus in a more efficient way.

    Original languageEnglish
    Pages (from-to)356-365
    Number of pages10
    JournalIEEE Systems Journal
    Issue number1
    Publication statusPublished - 2017 Mar 1



    • Collective decision making
    • data mining
    • social media
    • social roles
    • user model

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Electrical and Electronic Engineering

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