网络上的竞争性资源分配:考虑自信心演变的舆论动态

IF 14.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xia Chen , Zhaogang Ding , Yuan Gao , Hengjie Zhang , Yucheng Dong
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引用次数: 0

摘要

舆论的形成通常受到政府和企业等不同利益相关者的影响。最近,现实世界中出现了各种与舆论管理相关的问题,要求利益相关者在网络上战略性地分配资源,以实现其目标。要解决这些问题,就必须考虑舆论形成的动态过程。值得注意的是,在现有的舆论动态模型中,个人拥有的自信参数反映了他们对历史观点的坚持。然而,大多数现有研究都假设个体的自信心水平随时间推移保持不变,这无法准确捕捉人类行为的复杂性。针对这一缺陷,我们首先引入了一个自信心演化模型,其中包含两个影响因素:一个是群体伙伴的自信心水平,另一个是时间的流逝。此外,我们还提出了具有自信心演变的社会网络 DeGroot 模型,并进行了一些理论分析。此外,我们还提出了一个博弈模型,以确定网络中参与者的最优资源分配策略。最后,我们提供了敏感性分析、比较研究和案例研究。本文强调了将自信心演变纳入舆论动态过程的重要意义,其结果可为寻求改善网络上最优资源配置以更有效地管理舆论的参与者提供有价值的实践启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Competitive resource allocation on a network considering opinion dynamics with self-confidence evolution

The formation of public opinion is typically influenced by different stakeholders, such as governments and firms. Recently, various real-world problems related to the management of public opinion have emerged, necessitating stakeholders to strategically allocate resources on networks to achieve their objectives. To address this, it is imperative to consider the dynamics of opinion formation. Notably, in existing opinion dynamics models, individuals possess self-confidence parameters reflecting their adherence to historical opinions. However, most extant studies assume the individuals’ self-confidence levels remain constant over time, which cannot accurately capture the intricacies of human behavior. In response to this gap, we first introduce a self-confidence evolution model, which encompasses two influencing factors: the self-confidence levels of one's group mates and the passage of time. Furthermore, we present the social network DeGroot model with self-confidence evolution, and conduct some theoretical analyses. Moreover, we propose a game model to identify the optimal resource allocation strategies of players on a network. Finally, we provide sensitivity analyses, comparative studies, and a case study. This paper highlights the significance of incorporating self-confidence evolution into the process of opinion dynamics, and the results can provide valuable practical insights for players seeking to improve their optimal resource allocation on a network to more effectively manage public opinions.

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来源期刊
Information Fusion
Information Fusion 工程技术-计算机:理论方法
CiteScore
33.20
自引率
4.30%
发文量
161
审稿时长
7.9 months
期刊介绍: Information Fusion serves as a central platform for showcasing advancements in multi-sensor, multi-source, multi-process information fusion, fostering collaboration among diverse disciplines driving its progress. It is the leading outlet for sharing research and development in this field, focusing on architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome.
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