Opinion Dynamics Considering Matthew Effect With Time Delays and Stubborn Influence in Social Networks

IF 7.9 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-31 DOI:10.1109/TNSE.2025.3556379

Meng Li;Jinyuan Zhang;Long Jin

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引用次数: 0

Abstract

In social networks, stubborn individuals are resistant to changing their opinions or positions, affecting the trend of opinion evolution. Communication among individuals inherently involves time delays, which could lead to instability in information dissemination between individuals. To address these gaps in existing works, a new Matthew effect with time delays and stubborn influence (METS) model is proposed. In this paper, stubbornness coefficients are introduced to quantify individuals' adherence to their initial opinions, and a new approach to assess the speed of opinion development is proposed. Additionally, the social network is modeled as a distributed communication system that incorporates time delays to depict the connections between opinions. Furthermore, the

$k$

-winners-take-all (

$k$

-WTA) operation is employed as the feedback mechanism of the model to differentiate the winners and losers within the Matthew effect. Then, a thorough analysis of the model's convergence and stability is provided. Besides, numerical experiments demonstrate the flexibility and practicality of the METS model. Finally, extensive simulations are conducted to examine the influence of individual stubbornness on the dynamics of opinion evolution.

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考虑时滞和顽固影响下马太效应的社会网络舆论动态

在社交网络中，顽固的个体不愿意改变自己的观点或立场，从而影响了观点演变的趋势。个体之间的交流存在固有的时间延迟，这可能导致个体之间信息传播的不稳定性。为了解决现有研究中的这些空白，本文提出了一个新的带有时间延迟和顽固影响的马太效应（METS）模型。本文引入固执系数来量化个体对其初始意见的坚持程度，并提出了一种评估意见发展速度的新方法。此外，社交网络被建模为一个分布式通信系统，该系统包含时间延迟来描述意见之间的联系。此外，采用$k$-赢者通吃（$k$-WTA）操作作为模型的反馈机制，在马太效应中区分赢家和输家。然后，对模型的收敛性和稳定性进行了深入的分析。此外，数值实验也验证了METS模型的灵活性和实用性。最后，进行了大量的模拟，以检验个人固执对意见演变动态的影响。

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 Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.