Fake News Detection Using Machine Learning and Natural Language Processing

Abstract: The use of websites social media and online news platforms has made it possible to receive information quickly at the same time the amount of misleading and false news available online has increased checking every news article manually can be time-consuming this study therefore explores a machine learning-based method for automatically classifying news articles the proposed system uses the t fake news separate collections of fake and real news articles the news text is cleaned and converted into using term frequency-inverse document frequency tf-idf these features are given to a logistic regression classifier for binary assigns each article fake or real category on the test data the developed model obtained an accuracy of 9882 the results indicate that the selected combination of text performs well on in study keywords fake news detection machine learning natural language processing tf-idf logistic regression