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The influence of communication structure on opinion dynamics in social networks with multiple true states
Applied Mathematics and Computation ( IF 4 ) Pub Date : 2021-04-25 , DOI: 10.1016/j.amc.2021.126262
Aili Fang

In order to study the influence of communication structure on opinion dynamics in social networks with multiple true states, a social learning model is proposed in which the social network is composed of strongly connected communities and some uninformed individuals outside the communities. Multiple communities correspond to multiple underlying true states. At each time step, the individual in a community receives his private signal and updates his opinion to be a weighted linear combination of his own Bayesian posterior opinion and the opinions of his neighbors, while the uninformed individual outside the communities has no private signal and only takes the neighbors’ weighted average opinion as his own opinion. Simulation results show that in the social network environment with multiple true states, for the uninformed individual, the opinion will depend on the weighted average opinion of his neighbors, and for the individual in the strongly connected community, the opinion dynamics will depend on the communication types between communities. If communities are not connected, he will achieve asymptotic learning. If communities are unidirectionally connected, he will learn the true state of the root community. If communities are bidirectionally connected, his opinion will appear chaos phenomenon and oscillate within a certain range. So, in a society with multiple true states, the absence of communication between communities is conducive to asymptotic learning and bidirectional communications between communities will hinder asymptotic learning.



中文翻译:

交流结构对具有多个真实状态的社交网络中意见动态的影响

为了研究交流结构对具有多个真实状态的社交网络中意见动态的影响,提出了一种社交学习模型,其中社交网络由紧密连接的社区和社区之外的一些不知情的个人组成。多个社区对应于多个潜在的真实状态。在每个时间步长中,社区中的个人都会收到自己的私人信号,并将其意见更新为他自己的贝叶斯后验意见和邻居意见的加权线性组合,而社区外部的无知者则没有私人信号,只有将邻居的加权平均意见作为自己的意见。仿真结果表明,在具有多个真实状态的社交网络环境中,对于不知情的个人,意见将取决于邻居的加权平均意见,对于紧密联系的社区中的个人,意见动态将取决于社区之间的交流类型。如果社区没有连接,他将实现渐近学习。如果社区是单向连接的,那么他将学习根社区的真实状态。如果社区是双向连接的,他的意见将出现混乱现象并在一定范围内振荡。因此,在具有多个真实状态的社会中,社区之间缺乏交流会有助于渐近学习,而社区之间的双向交流则会阻碍渐进学习。意见动态将取决于社区之间的交流类型。如果社区没有连接,他将实现渐近学习。如果社区是单向连接的,那么他将学习根社区的真实状态。如果社区是双向连接的,他的意见将出现混乱现象并在一定范围内振荡。因此,在具有多个真实状态的社会中,社区之间缺乏交流会有助于渐近学习,而社区之间的双向交流则会阻碍渐进学习。意见动态将取决于社区之间的交流类型。如果社区没有连接,他将实现渐近学习。如果社区是单向连接的,那么他将学习根社区的真实状态。如果社区是双向连接的,他的意见将出现混乱现象并在一定范围内振荡。因此,在具有多个真实状态的社会中,社区之间缺乏交流会有助于渐近学习,而社区之间的双向交流则会阻碍渐进学习。如果社区是双向连接的,他的意见将出现混乱现象并在一定范围内振荡。因此,在具有多个真实状态的社会中,社区之间缺乏交流有利于渐近学习,而社区之间的双向交流则会阻碍渐进学习。如果社区是双向连接的,他的意见将出现混乱现象并在一定范围内振荡。因此,在具有多个真实状态的社会中,社区之间缺乏交流会有助于渐近学习,而社区之间的双向交流则会阻碍渐进学习。

更新日期:2021-04-26
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