Classifying Fake News Articles using Natural Language Processing and Supervised Learning Estimator

Abstract

In the modern days, as the internet is present everywhere, each and every onedepends on variety of online sources for news. As the usage of Facebook, Twitter and many social media platforms, spreading of news is increasing rapidly among millions of people in a very short time span.Initially, the distribution of fake news spreads across the social media platforms and later finds it ways and reaches onto media such as Traditional Television and radio news.In this paper, the results of the fake news identification is studied and presented. Natural language processing, Naïve Bayes classifier or algorithm and SciPy tools are used to identify whether the news is real or fake by extracting the quotes from the news articles and estimate the likelihood percentage from the extracted quotes.