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arXiv 2104.14477physics.soc-ph
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多维连续意见模型的解析表示

Analytical formulation for multidimensional continuous opinion models

Lucia Pedraza, Juan Pablo Pinasco, Nicolas Saintier, Pablo Balenzuela

摘要:

通常,意见形成模型假设个人对给定主题的意见会因与他人的互动而改变。然而,个人可以在不同的主题中有不同的观点,因此n维模型最适合处理这些情况。虽然已经有许多努力来开发一维的意见模型的分析模型,很少有人注意到多维的。在这项工作中,我们开发了一种分析方法,用于连续意见的多维模型,其中维度可以相关或不相关。我们发现,对于任何通用的互惠代理之间的相互作用,初始意见分布的平均值是保守的。此外,积极的社会影响力的互动机制,意见分布的方差随着时间的推移而减少,系统收敛到一个delta分布函数。特别是,我们计算的收敛时间时,代理人在相互作用后,在一个离散的数量更接近,相关和不相关的情况下,表现出明显的差异。

英文摘要:

Usually, opinion formation models assume that individuals have an opinion about a given topic which can change due to interactions with others. However, individuals can have different opinions in different topics and therefore n-dimensional models are best suited to deal with these cases. While there have been many efforts to develop analytical models for one dimensional opinion models, less attention has been paid to multidimensional ones. In this work, we develop an analytical approach for multidimensional models of continuous opinions where dimensions can be correlated or uncorrelated. We show that for any generic reciprocal interactions between agents, the mean value of initial opinion distribution is conserved. Moreover, for positive social influence interaction mechanisms, the variance of opinion distributions decreases with time and the system converges to a delta distributed function. In particular, we calculate the convergence time when agents get closer in a discrete quantity after interacting, showing a clear difference between correlated and uncorrelated cases.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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