Dynamic Compromise Behavior Driven Bidirectional Feedback Mechanism for Group Consensus With Overlapping Communities in Social Network

IF 8.6 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Tiantian Gai;Jian Wu;Francisco Chiclana;Mingshuo Cao;Ronald R. Yager
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引用次数: 0

Abstract

In social network group decision making (SN-GDM), overlapping communities are special community structures that can assist opinion interaction to reach group consensus. However, the specific mechanisms of how overlapping structures facilitate community interaction need to be further explored. In addition, the compromise behavior of decision makers (DMs) is conducive to group consensus, but it is usually fixed at the same value, and then it need further research the characteristic of the dynamics compromise limits. To this end, the overlapping community structures under DMs’ trust network is detected. Then, the effect of community overlap in social networks on community interaction is explored. Meanwhile, a limited compromise function is built based on prospect theory to describe the dynamic compromise behavior of communities. Hence, a dynamic compromise behavior driven bidirectional feedback mechanism with overlapping communities is proposed in the context of SN-GDM, and an illustrative example with comparative analysis is provided to testify the advantages of proposed method. It is proved that overlapping communities can improve the compromise willingness compared to nonoverlapping communities, indicating that overlapping communities can serve as a bridge to facilitate interaction, and the dynamic compromise behavior can more realistically describe the real behavior of DMs. In general terms, the proposed method provides a solution to the consensus reaching issue of SN-GDM from a new perspective. Specifically, it can be applied to real-life application scenarios, such as group recommendation to recommend acceptable solutions for social network group users.
社交网络中重叠群体达成群体共识的动态妥协行为驱动双向反馈机制
在社会网络群体决策(SN-GDM)中,重叠社群是一种特殊的社群结构,可以帮助意见互动以达成群体共识。然而,重叠结构如何促进群体互动的具体机制还有待进一步探讨。此外,决策者(DMs)的妥协行为有利于达成群体共识,但其妥协值通常固定不变,这就需要进一步研究动态妥协极限的特征。为此,本文检测了 DMs 信任网络下的重叠社群结构。然后,探讨社交网络中社区重叠对社区互动的影响。同时,基于前景理论建立了有限妥协函数来描述社区的动态妥协行为。因此,在 SN-GDM 的背景下,提出了一种具有重叠社群的动态妥协行为驱动的双向反馈机制,并提供了一个对比分析的示例来证明所提方法的优势。研究证明,与非重叠群落相比,重叠群落可以提高妥协意愿,这表明重叠群落可以作为促进交互的桥梁,动态妥协行为可以更真实地描述 DM 的真实行为。总的来说,所提出的方法从一个新的角度为 SN-GDM 的共识达成问题提供了一个解决方案。具体来说,它可以应用于现实生活中的应用场景,例如为社交网络群体用户推荐可接受的解决方案的群体推荐。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Systems Man Cybernetics-Systems
IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS
CiteScore
18.50
自引率
11.50%
发文量
812
审稿时长
6 months
期刊介绍: The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.
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