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Detecting Fake News using PA Classifier

Amer Khan, Divyansh Gehlot, Omkar Kumbhar, Neha Mahajan

Abstract


Information, i.e., news, must be legitimate, which is frequently discovered in corrupted versions, necessitating the need for a method of distinguishing actual news from any possible false news. The objective of fake news is to spread misinformation by piquing the interest of readers with attractive headlines or images that look believable, therefore, we need to include auxiliary information, such as author and publisher, to verify the credibility of the news. As a human, one may readily distinguish between authentic and false news by applying logic and looking at the source. But on the machine level, there is an urgent need for some software which can consistently pick out which piece of information is fake. As a result, it is currently one of the most investigated areas. Various machine learning algorithms with varied degrees of accuracy can be used to detect false news. As per the research conducted till date, there is still a lot of ground to cover in this field.

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References


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