社交网络中的意见两极分化

N. Loy, Matteo Raviola, A. Tosin
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引用次数: 7

摘要

在本文中,我们提出了一种考虑个体一般连通性分布的社会网络意见形成的玻尔兹曼型动力学描述。我们考虑了受Sznajd模型和相关简化启发的意见交换过程,但我们不假设个体在规则晶格上相互作用。相反,我们用统计方法来描述社会网络的结构,假设一个给定个体的接触人数决定了他们的意见达到并影响另一个个体意见的概率。从系统的动力学描述出发,研究了平均意见的演化过程,得到了平均意见发生极化转换的精确解析条件,即初始平均意见与渐近平均意见之间的符号变化。特别是,我们证明了初始意见与个体连通性之间的非零相关是观察极化转换的必要条件。最后,我们通过蒙特卡洛模拟社会网络上的随机意见交换过程来验证我们的分析结果。本文是“社会和经济的动态交换模型”主题的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Opinion polarization in social networks
In this paper, we propose a Boltzmann-type kinetic description of opinion formation on social networks, which takes into account a general connectivity distribution of the individuals. We consider opinion exchange processes inspired by the Sznajd model and related simplifications but we do not assume that individuals interact on a regular lattice. Instead, we describe the structure of the social network statistically, assuming that the number of contacts of a given individual determines the probability that their opinion reaches and influences the opinion of another individual. From the kinetic description of the system, we study the evolution of the mean opinion, whence we find precise analytical conditions under which a polarization switch of the opinions, i.e. a change of sign between the initial and the asymptotic mean opinions, occurs. In particular, we show that a non-zero correlation between the initial opinions and the connectivity of the individuals is necessary to observe polarization switch. Finally, we validate our analytical results through Monte Carlo simulations of the stochastic opinion exchange processes on the social network. This article is part of the theme issue ‘Kinetic exchange models of societies and economies’.
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