Fake News Detection using Machine Learning

Abstract

Fake News has become one of the major problems in the existing society. Fake News has high potential to change opinions, facts and can be the most dangerous weapon in influencing society. The proposed project uses NLP techniques for detecting the 'fake news', that is, misleading news stories which come from non-reputable sources. By building a model based on a K-Means clustering algorithm, the fake news can be detected. The data science community has responded by taking actions against the problem. It is impossible to determine whether the news was real or fake accurately. So, the proposed project uses the datasets that are trained using the count vectorizer method for the detection of fake news and its accuracy will be tested using machine learning algorithms.