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There has been a large surge of fake news in recent times due to the immense use of social media and online news media. It has become much easier to spread fake news then how it used to be earlier. This kind of fake news when spread may have a severe effect. Hence it is extremely essential that certain measures should be taken in order to reduce or distinguish between real and fake news. This paper presents a survey on fake news detection. In addition, this paper proposes a model that classifies unreliable news into real and fake news after computing a score and will be able to distinguish between real and fake news based on various parameters obtained from a Uniform Resource Locator (URL). The model proposed will use various MachineLearning and Natural Language Processing (NLP) techniques to achieve maximum accuracy.
Gaonkar et al. (Fri,) studied this question.
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