PSent20: An Effective Political Sentiment Analysis with Deep Learning Using Real-Time Social Media Tweets

Apar Garg, Rohit Kumar Kaliyar
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引用次数: 2

Abstract

In the current era of computing, the use of social networking sites like Twitter and Facebook, is growing significantly over time. People from different cultures and backgrounds share vast volumes of textual comments that show their viewpoints on several aspects of life and make them available to all for commenting. Monitoring real social media activities has now become a prime concern for politicians in understanding their social image. In this paper, we are going to analyse the tweets of various social media platforms regarding two prominent political leaders and classify them as positive, negative or neutral using Machine Learning and Deep Learning methods. We have proposed a Deep Learning approach for a better solution. Our proposed model has provided state-of-the-art results using Deep Learning models.
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使用实时社交媒体tweet的深度学习有效的政治情绪分析
在当今的计算机时代,像Twitter和Facebook这样的社交网站的使用随着时间的推移而显著增长。来自不同文化和背景的人们分享了大量的文本评论,这些评论显示了他们对生活的几个方面的观点,并使所有人都可以评论。监控真实的社交媒体活动现在已经成为政客们了解自己社会形象的首要关注点。在本文中,我们将分析各种社交媒体平台上关于两位杰出政治领导人的推文,并使用机器学习和深度学习方法将其分类为积极,消极或中立。为了更好的解决方案,我们提出了一种深度学习方法。我们提出的模型使用深度学习模型提供了最先进的结果。
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