Fake News Detection Using Machine Learning

Abstract

The rapid use of social media sites like Facebook and Twitter, along with the advent of the Internet, has allowed for the dissemination of information at a level never before seen... More people than ever before are making and sharing content on social media, and unfortunately, some of it is false or otherwise unfounded. It is difficult to automate the process of determining if a written article contains misinformation or disinformation. Prior to reaching a conclusion on an article's veracity, even a domain expert must consider several factors. Automated news article categorization is our proposed usage of a machine learning ensemble technique in this study. In this study, we examine various linguistic characteristics that can be used to distinguish between real and fake news. Taking use of these features, we evaluate the performance of a variety of machine learning algorithms trained using various ensemble methods on four real-world datasets. Results from experiments show that our suggested ensemble learner method outperforms individual learners. Keywords: World Wide Web, Social Media platforms, Information distribution, Content Sharing Textual Features, Machine Learning, Machine Learning ensemble technique, Real-worlds dataset etc.