社交网络下行为引导的多尺度双层群共识建模

doi:10.11896/jsjkx.250500066

计算机科学 ›› 2026, Vol. 53 ›› Issue (4): 180-187.doi: 10.11896/jsjkx.250500066

• 数据库&大数据&数据科学 • 上一篇下一篇

社交网络下行为引导的多尺度双层群共识建模

常文霞¹, 张超^1,2,3, 李文涛^4,5, 詹建明⁶, 李德玉^1,2

1 山西大学计算机与信息技术学院太原 030006
2 计算智能与中文信息处理教育部重点实验室(山西大学) 太原 030006
3 山西太行实验室有限公司/太行山西省实验室太原 030000
4 西南大学人工智能学院重庆 400715
5 宜宾西南大学研究院四川宜宾 644000
6 湖北民族大学数学与统计学院湖北恩施 445000

收稿日期:2025-05-16 修回日期:2025-07-19 出版日期:2026-04-15 发布日期:2026-04-08
通讯作者: 张超(czhang@sxu.edu.cn)
作者简介:(18536202190@163.com)
基金资助:
国家自然科学基金(62272284,62473241,12201518,12271146,12161036);中央引导地方科技发展资金(YDZJSX2024D015);太行山西省实验室开放课题专项资金(THYF-KFKT-25010500);山西省科技合作交流专项(基于量子多粒度群共识的可信数据空间隐私增强技术研究);三晋英才青年拔尖人才项目;四川省科技计划资助(2025ZNSFSC0806);重庆市教委科技研究计划(KJZD-K20250020);山西大学文瀛青年学者

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

CHANG Wenxia¹, ZHANG Chao^1,2,3, LI Wentao^4,5, ZHAN Jianming⁶, LI Deyu^1,2

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 Published:2026-04-15 Online: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.

摘要/Abstract

摘要： 作为智能化时代复杂决策的关键要素,群共识旨在通过观点交互缓解冲突,以达成一致意见。为弥补单尺度无法全面反映信息特征的不足,解决行为异质性及非公平性导致的冲突,在多尺度信息系统下构建社交网络行为引导的双层共识模型。首先,提出基于Choquet积分的尺度融合模型,采用模糊测度刻画尺度间的非线性交互作用,实现尺度间的深度耦合。其次,利用社交网络评估决策者行为,通过可靠性和传播力度量内在表现,利用互动密度和合作强度度量外在表现,为行为引导策略提供量化依据。然后,基于行为特征指标构建多粒度视角下的双层共识模型,结合优化模型与规则机制平衡意见调整的最小代价与最大公平,优化资源配置。此外,从基数和序数角度设计结合得分函数和序数排列的评分函数,突破传统评价单一维度局限。最后,利用携程平台上5A级晋祠景区的在线评论,对景区服务质量进行决策分析。

关键词: 多粒度, 多尺度, 群共识, 社交网络, 公平行为

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

中图分类号:

TP391

常文霞, 张超, 李文涛, 詹建明, 李德玉. 社交网络下行为引导的多尺度双层群共识建模[J]. 计算机科学, 2026, 53(4): 180-187. https://doi.org/10.11896/jsjkx.250500066

CHANG Wenxia, ZHANG Chao, LI Wentao, ZHAN Jianming, LI Deyu. Modeling of Behavior-guided Multi-scale Bi-level Group Consensus Under Social Networks[J]. Computer Science, 2026, 53(4): 180-187. https://doi.org/10.11896/jsjkx.250500066

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社交网络下行为引导的多尺度双层群共识建模

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

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