Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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An Empirical Study of Absolute-Fairness Maximal Balanced Cliques Detection Based on Signed Attribute Social Networks: Considering Fairness and Balance

  • Yixuan Yang (Dept. of Software Convergence, Soonchunhyang University) ;
  • Sony Peng (Dept. of Software Convergence, Soonchunhyang University) ;
  • Doo-Soon Park (Dept. of Software Convergence, Soonchunhyang University) ;
  • Hye-Jung Lee (Institute for Artificial Intelligence & Software, Soonchunhyang University) ;
  • Phonexay Vilakone (Dept. of Computer Engineering & Information Technology, National University of Laos)
  • Received : 2022.08.08
  • Accepted : 2023.03.18
  • Published : 2024.04.30
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Abstract

Amid the flood of data, social network analysis is beneficial in searching for its hidden context and verifying several pieces of information. This can be used for detecting the spread model of infectious diseases, methods of preventing infectious diseases, mining of small groups and so forth. In addition, community detection is the most studied topic in social network analysis using graph analysis methods. The objective of this study is to examine signed attributed social networks and identify the maximal balanced cliques that are both absolute and fair. In the same vein, the purpose is to ensure fairness in complex networks, overcome the "information cocoon" bottleneck, and reduce the occurrence of "group polarization" in social networks. Meanwhile, an empirical study is presented in the experimental section, which uses the personal information of 77 employees of a research company and the trust relationships at the professional level between employees to mine some small groups with the possibility of "group polarization." Finally, the study provides suggestions for managers of the company to align and group new work teams in an organization.

Keywords

Acknowledgement

This research was supported by BK21 Fostering Outstanding Universities for Research (No. 5199990914048) and the National Research Foundation of Korea (No. NRF-2022R1A2C1005921). This paper is the extended version of the Annual Spring Conference of KIPS (ASK 2022) held in Seoul, Republic of Korea dated May 19-21, 2022 [22].

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