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A Hierarchy of Linear Threshold Models for the Spread of Political Revolutions on Social Networks

机译:政治传播的线性门槛模型层次   社交网络革命

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摘要

We study a linear threshold agent-based model (ABM) for the spread ofpolitical revolutions on social networks using empirical network data. Wepropose new techniques for building a hierarchy of simplified ordinarydifferential equation (ODE) based models that aim to capture essential featuresof the ABM, including effects of the actual networks, and give insight in theparameter regime transitions of the ABM. We relate the ABM and the hierarchy ofmodels to a population-level compartmental ODE model that we proposedpreviously for the spread of political revolutions [1], which is shown to bemathematically consistent with the proposed ABM and provides a way to analyzethe global behaviour of the ABM. This consistency with the linear threshold ABMalso provides further justification a posteriori for the compartmental model of[1]. Extending concepts from epidemiological modelling, we define a basicreproduction number $R_0$ for the linear threshold ABM and apply it to predictABM behaviour on empirical networks. In small-scale numerical tests weinvestigate experimentally the differences in spreading behaviour that occurunder the linear threshold ABM model when applied to some empirical online andoffline social networks, searching for quantitative evidence that politicalrevolutions may be facilitated by the modern online social networks of socialmedia.
机译:我们使用经验网络数据研究基于线性阈值主体的模型(ABM),用于在社会网络上传播政治革命。我们提出了一种新的技术,用于建立基于简化的常微分方程(ODE)的模型的层次结构,旨在捕获ABM的基本特征,包括实际网络的影响,并深入了解ABM的参数范围转换。我们将ABM和模型层次结构与我们先前为政治革命的传播而提出的人口级隔间ODE模型相关联[1],这在数学上与所提议的ABM一致,并提供了一种分析ABM全局行为的方式。与线性阈值ABM的一致性也为[1]的隔室模型提供了进一步的证明。扩展了流行病学建模的概念,我们为线性阈值ABM定义了基本复制数$ R_0 $,并将其应用于经验网络上的ABM行为预测。在小规模的数值测试中,我们通过实验研究了线性阈值ABM模型在应用于一些经验性在线和离线社交网络时在传播行为上的差异,以寻找定量证据证明现代社会媒体在线社交网络可以促进政治革命。

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