Modified Hegselmann-Krause Model for Enhancing Opinion Diversity in Social Networks

被引:0
作者
Cheng, Chun [1 ]
Gu, Jiahao [1 ]
Lu, Siyan [1 ]
Ding, Weiping [1 ]
机构
[1] Nantong Univ, Sch Artificial Intelligence & Comp Sci, Nantong 226019, Jiangsu, Peoples R China
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Cultural differences; Stochastic processes; Solid modeling; Social groups; Multi-agent systems; Diversity schemes; Opinion dynamics; social conformity; uniqueness theory; bounded confidence; strong diversity; DYNAMICS; CONSENSUS;
D O I
10.1109/ACCESS.2024.3467225
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A goal of opinion dynamics modelers has long been to find a social science based model that generates strong diversity: smooth, stable, possibly multi-modal distributions of opinions. However, the classic Hegselmann-Krause (HK) model, which relies on similarity assumptions, is often criticized for producing only weak diversity. Here, weak diversity refers to the eventual convergence of group into several opinion clusters, where the gap between opinion clusters is limited by the confidence interval $\varepsilon $ , and all individuals within the same cluster share a single opinion. To address this limitation, this paper proposes a modified HK model (MHK) that incorporates social conformity and uniqueness theory from social psychology to enhance opinion diversity within the network. Social conformity theory accounts for the discrepancy between individuals' expressed opinions and their implicit opinions, while uniqueness theory establishes a new lower bound for individuals' confidence intervals. Our findings demonstrate that social conformity and uniqueness collectively promote strong diversity both within and between clusters. Consequently, our modified model effectively addresses the limitations of the classic HK model, thereby improving its capacity to capture strong diversity in opinion dynamics.
引用
收藏
页码:140715 / 140721
页数:7
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