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Human Action Prediction Using Sentiment Analysis on Social Networks

机译:基于社交网络的情感分析的人类行为预测

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There is a rapid increase of mass demonstrations in different locations worldwide triggered by social networks discussions, as witnessed in the USA, Egypt, and South Africa. This paper challenges the underutilization of social media to detect people's' mood and to predict their actions based on their sentiments. Recent published work has demonstrated utility of sentiments on Twitter to predict outcomes of different events, so to come up with the geographical action prediction tool the authors utilized geocodes, sentiment analysis, probability theory, and logistic regression. The tool informs relevant authorities like governments to know the state of people's moods. Entities like business enterprises also benefit from this tool in their plans, especially in avoiding unnecessary costs due to infrastructure destruction.
机译:如美国,埃及和南非所见证的,由于社交网络的讨论,全球各地的大规模示威活动迅速增加。本文对社交媒体利用不足以挑战人们的情绪并根据其情绪预测他们的行为提出了挑战。最近发表的工作证明了Twitter上的情绪可用于预测不同事件的结果,因此,作者提出了地理行为预测工具,利用地理编码,情绪分析,概率论和逻辑回归。该工具通知政府等相关部门了解人们的情绪状态。诸如企业这样的实体也从其计划中受益于此工具,尤其是在避免由于基础架构破坏而产生不必要的成本方面。

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