Prediction of Fake Tweets Using Machine Learning Algorithms

M. Sreedevi, G. Vijay Kumar, K. Kiran Kumar, B. Aruna, Arvind Yadav
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Abstract

Social networking sites will attract millions of users around the globe. Internet media is becoming popular for news consumption because of its ease, simple access and fast spreading of data takes to consume news from social media. Fake news on social media is making an appearance that is attracting a huge attention. This kind of situation could bring a great conflict in real time. The false news impacts extremely negative on society, particularly in social, commercial, political world, also on individuals. Hence detection of fake news on social media became one of the emerging research topic and technically challenging task due to availability of tools on social media. In this paper various machine learning techniques are used to predict fake news on twitter data. The results shown by using these techniques are more accurate with better performance.
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使用机器学习算法预测假推文
社交网站将吸引全球数以百万计的用户。网络媒体正变得越来越流行的新闻消费,因为它的方便,简单的访问和快速传播的数据需要从社交媒体消费新闻。社交媒体上的假新闻正在出现,吸引了巨大的关注。这种情况可能会在现实中带来巨大的冲突。虚假新闻对社会,特别是在社会,商业,政治世界,以及个人产生了极其负面的影响。因此,由于社交媒体上工具的可用性,社交媒体上的假新闻检测成为新兴的研究课题之一,也是技术上具有挑战性的任务。在本文中,使用各种机器学习技术来预测twitter数据上的假新闻。使用这些技术得到的结果精度更高,性能更好。
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