基于平均场博弈的有影响力个体与强组织群体共存的大规模群体意见演化

IF 6.7 2区 计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY
Lu Ren;Yuxin Jin;Wang Yao;Xiao Zhang;Guanghui Jiao
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引用次数: 0

摘要

随着网络媒体的蓬勃发展,关键意见领袖和水军的盛行导致了用户意见的意外演变。因此,研究影响力个体与强组织群体并存的大规模群体的舆论演化问题是有价值和意义的。针对上述问题,本文基于均场博弈理论,创新性地提出了多领导者多群体-追随者斯塔克尔伯格均场博弈(MLMPF-SMFG)模型来描述舆论演化场景,其中有影响力的个体被视为领导者,正常群体和强组织群体被视为追随者群体。此外,出于通用性考虑,强组织个体类型被分为三种典型类型:宣传者、间谍和中立者。然后,通过邻接法推导出最优策略,并用前后向随机微分方程求解。给出了斯塔克尔伯格均衡(SE)存在和唯一的充分条件,并证明了有限系统的近似 SE。最后,对两个有影响力的个体和两个普通群体的意见演变进行了模拟实验,证明了所提出的 MLMPF-SMFG 模型的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Large-Scale Group Opinion Evolution With Coexistence of Influential Individuals and Strongly Organized Groups Based on Mean Field Games
With the vigorous development of online media, the prevalence of key opinion leaders and water armies has led to unexpected evolutions of users' opinions. Therefore, it is valuable and interesting to investigate the opinion evolution problem for large-scale groups with the coexistence of influential individuals and strongly organized groups. For the above problem, based on the mean-field game theory, this article innovatively proposes a multi-leader multi-population-follower Stackelberg mean field game (MLMPF-SMFG) model to describe the opinion evolution scenario, in which influential individuals are regarded as leaders, normal and strongly organized groups are regarded as follower populations. Moreover, for generality, the types of strongly organized individuals are classified into three typical types: propagandists, spies, and neutrals. Then, the optimal strategies are derived via the adjoint method and solved by forward–backward stochastic differential equations. Sufficient conditions for the existence and uniqueness of the Stackelberg equilibrium (SE) are given, and the approximate SE of the finite system is proven. Finally, simulation experiments on the opinion evolutions of two influential individuals and two ordinary groups are performed to demonstrate the feasibility and effectiveness of the proposed MLMPF-SMFG model.
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来源期刊
IEEE Transactions on Network Science and Engineering
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.
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