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

*この研究の対応する著者

研究成果: Article査読

13 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)356-365
ページ数10
ジャーナルIEEE Systems Journal
11
1
DOI
出版ステータスPublished - 2017 3月

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 情報システム
  • コンピュータ サイエンスの応用
  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学

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