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Forecasting Country Stability in North Africa

机译:预测北非的国家稳定

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We develop a novel approach to predict certain type of stability events (battles, battles won by a government, riots/protests, violence against civilians) in countries by monitoring the content of a mix of traditional news, blog, and social media data. Specifically, we show that by monitoring sentiment on both pro- and anti-government entities within a country, even with a relative paucity of longitudinal data (36 time points), we can predict these stability related events with just over 80% classification accuracy. We report on our methods, together with a description of a prototype system called Sentibility that tracks country stability related events. In addition, we cast light on the key entities, sentiments on whom were correlated strongly (positively or negatively) by both Pearson and Spearman correlation coefficients, with such stability events in 3 countries: Egypt, Morocco, and Sudan.
机译:我们通过监测传统新闻,博客和社交媒体数据的组合的内容,我们制定了一种新的一种新的方法来预测各种类型的稳定事件(由政府,骚乱/抗议,暴力,暴力抵御平民)。具体而言,我们表明,即使在纵向数据(36个时间点)的相对缺乏相对缺乏的情况下,我们也可以通过超过80%的分类准确性来预测这些稳定相关事件的主力。我们报告我们的方法,以及涉及跟踪国家稳定相关事件的理发系统的描述。此外,我们在主要实体中投射了光线,Pearson和Spearman相关系数的关键实体的情绪(积极或积极地或负面),其中3个国家/地区的稳定事件:埃及,摩洛哥和苏丹。

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