Social network group decision-making model considering interactions between trust relationships and opinion evolution

群体决策 群(周期表) 控制论 计算机科学 决策模型 管理科学 人工智能 知识管理 运筹学 数理经济学 理论计算机科学 社会心理学 心理学 数学 经济 有机化学 化学
作者
J. Ma,Tong Wu
出处
期刊:Kybernetes [Emerald (MCB UP)]
标识
DOI:10.1108/k-05-2023-0930
摘要

Purpose Social network group decision-making (SNGDM) has rapidly developed because of the impact of social relationships on decision-making behavior. However, not only do social relationships affect decision-making behavior, but decision-making behavior also affects social relationships. Such complicated interactions are rarely considered in current research. To bridge this gap, this study proposes an SNGDM model that considers the interaction between social trust relationships and opinion evolution. Design/methodology/approach First, the trust propagation and aggregation operators are improved to obtain a complete social trust relationship among decision-makers (DMs). Second, the evolution of preference information under the influence of trust relationships is measured, and the development of trust relationships during consensus interactions is predicted. Finally, the iteration of consensus interactions is simulated using an opinion dynamics model. A case study is used to verify the feasibility of the proposed model. Findings The proposed model can predict consensus achievement based on a group’s initial trust relationship and preference information and effectively captures the dynamic characteristics of opinion evolution in social networks. Originality/value This study proposes an SNGDM model that considers the interaction of trust and opinion. The proposed model improves trust propagation and aggregation operators, determines improved preference information based on the existing trust relationships and predicts the evolution of trust relationships in the consensus process. The dynamic interaction between the two accelerates DMs to reach a consensus.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
今后应助666采纳,获得10
刚刚
Lucas应助负灵采纳,获得10
2秒前
一平发布了新的文献求助10
3秒前
量子星尘发布了新的文献求助10
3秒前
七七发布了新的文献求助10
4秒前
4秒前
脑洞疼应助幸福妙柏采纳,获得10
4秒前
财财发布了新的文献求助20
5秒前
5秒前
NexusExplorer应助轻松元柏采纳,获得10
6秒前
6秒前
晓静完成签到 ,获得积分10
6秒前
6秒前
黙宇循光完成签到 ,获得积分10
8秒前
Akim应助bjwh采纳,获得10
9秒前
淡淡的酸奶完成签到,获得积分10
10秒前
10秒前
10秒前
11秒前
21发布了新的文献求助10
11秒前
11秒前
14秒前
15秒前
李国明发布了新的文献求助10
16秒前
ding应助zhoujingya采纳,获得10
17秒前
18秒前
早点毕业完成签到,获得积分10
18秒前
20秒前
20秒前
不鞠一格发布了新的文献求助10
21秒前
今后应助沉小墨采纳,获得10
21秒前
在水一方应助怡然新之采纳,获得10
22秒前
量子星尘发布了新的文献求助10
23秒前
寻道图强应助Takahara2000采纳,获得30
24秒前
清新的S发布了新的文献求助10
25秒前
大模型应助一平采纳,获得10
25秒前
26秒前
金博洋发布了新的文献求助10
27秒前
嘟噜嘟噜应助Tonson采纳,获得40
27秒前
轻松元柏完成签到,获得积分20
28秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Social Work Ethics Casebook: Cases and Commentary (revised 2nd ed.).. Frederic G. Reamer 1070
Alloy Phase Diagrams 1000
Introduction to Early Childhood Education 1000
2025-2031年中国兽用抗生素行业发展深度调研与未来趋势报告 1000
List of 1,091 Public Pension Profiles by Region 891
Historical Dictionary of British Intelligence (2014 / 2nd EDITION!) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5425091
求助须知:如何正确求助?哪些是违规求助? 4539235
关于积分的说明 14166259
捐赠科研通 4456389
什么是DOI,文献DOI怎么找? 2444167
邀请新用户注册赠送积分活动 1435182
关于科研通互助平台的介绍 1412539