Computer Science

Computer Science ›› 2026, Vol. 53 ›› Issue (4): 180-187.doi: 10.11896/jsjkx.250500066

• Database & Big Data & Data Science • Previous Articles     Next Articles

Modeling of Behavior-guided Multi-scale Bi-level Group Consensus Under Social Networks

CHANG Wenxia1, ZHANG Chao1,2,3, LI Wentao4,5, ZHAN Jianming6, LI Deyu1,2   

  1. 1 School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China
    2 Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education(Shanxi University), Taiyuan 030006, China
    3 Shanxi Taihang Laboratory Co., Ltd./Taihang Laboratory in Shanxi Province, Taiyuan 030000, China
    4 College of Artificial Intelligence, Southwest University, Chongqing 400715, China
    5 Yibin Academy of Southwest University, Yibin, Sichuan 644000, China
    6 School of Mathematics and Statistics, Hubei Minzu University, Enshi, Hubei 445000, China
  • Received:2025-05-16 Revised:2025-07-19 Online:2026-04-15 Published:2026-04-08
  • About author:CHANG Wenxia,born in 2003,master,is a member of CCF(No.Z4337G).Her main research interests include data mining,intelligent decision and traffic flow prediction.
    ZHANG Chao,born in 1989,Ph.D.His main research interests include data mining,intelligent decision and traffic flow prediction.
  • Supported by:
    National Natural Science Foundation of China(62272284,62473241,12201518,12271146,12161036),Central Government Guides Local Science and Technology Innovation(YDZJSX2024D015),Open Project Special Fund of Taihang Laboratory in Shanxi Province(THYF-KFKT-25010500),Science and Technology Cooperation and Exchange Special Projects of Shanxi(Research on Privacy Enhancement Technology for Trusted Data Space Based on Quantum Multi-Granularity Group Consensus),Top Young Talents of Shanxi “Three Jin” Talents Program,Sichuan Science and Technology Program(2025ZNSFSC0806),Science and Technology Research Program of Chongqing Education Commission(KJZD-K20250020) and Wenying Young Scholars of Shanxi University.

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Abstract: As a key element of complex decision-making in the era of intelligence,group consensus aims to alleviate conflicts and reach a consensus by the interaction of opinions.To address the limitation of single-scale methods in fully reflecting information characteristics and to resolve conflicts arising from behavioral heterogeneity and unfairness,a behavior-guided multi-scale bi-level group consensus model is constructed.Firstly,a Choquet integral-based scale fusion model is proposed,where fuzzy measures characterize non-linear scale interactions and enable deep coupling.Next,the social network evaluation is applied to assess decision-maker behavior by internal performances measured by reliability and propagation strengths,and external performances measured by interaction density and cooperation intensity,providing a quantitative basis for behavior-guided strategies.Then,a bi-level consensus model under multi-granularity perspectives is constructed based on behavioral feature indicators,combining optimization models with rule mechanisms to balance the minimum cost and maximum fairness of opinion adjustments,optimizing resource allocation.Additionally,scoring functions that integrate cardinal with ordinal rankings are designed from both cardinal and ordinal perspectives,breaking through the limitations of traditional single-dimensional evaluations.Finally,a decision analysis of the ser-vice quality of the 5A-rated Jinci Scenic Area is performed based on online reviews from the Ctrip platform.

Key words: Multi-granularity, Multi-scale, Group consensus, Social network, Fair behavior

CLC Number: 

  • TP391
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