Arab Spring: from newspaper
Arab Spring: from newspaper
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阿拉伯之春：摘自报纸
DOI：
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发表时间：
2014
影响因子：
2.8
通讯作者：
J. Pfeffer
中科院分区：
文献类型：
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作者：
K. Joseph;Kathleen M. Carley;David Filonuk;Geoffrey P. Morgan;J. Pfeffer
基于主体的仿真模型是解释社会行为和预测社会变化的重要方法。然而，使用这种模型的一个主要缺点是，它们很难为特定的情况实例化，因此很少被重用。我们描述了一种文本挖掘网络分析方法，用于快速实例化一个模型，该模型用于预测基于大量参与者的社会和文化特征的革命和暴力倾向。我们使用基于代理的动态网络框架、Construct和与阿拉伯之春相关的16个国家的报纸数据来说明我们的方法。我们评估了基本模型在阿拉伯之春期间独立运行的20个月的总体准确性，观察到尽管预测导致了几个假阳性，但该模型能够在政府被成功推翻的四个国家中的三个国家发生革命之前预测革命。
Agent-based simulation models are an important methodology for explaining social behavior and forecasting social change. However, a major drawback to using such models is that they are difficult to instantiate for specific cases and so are rarely reused. We describe a text-mining network analytic approach for rapidly instantiating a model for predicting the tendency toward revolution and violence based on social and cultural characteristics of a large collection of actors. We illustrate our approach using an agent-based dynamic network framework, Construct, and newspaper data for the 16 countries associated with the Arab Spring. We assess the overall accuracy of the base model across independent runs for 20 different months during the Arab Spring, observing that although predictions led to several false positives, the model is able to predict revolution before it occurs in three of the four nations in which the government was successfully overthrown.