Fake News Detection Using Machine Learning

Abstract

Abstract: The advent of the World Wide Web, along with the rapid adoption of social networks such as Twitter and Facebook, paved the way for unprecedented information dissemination in human history. Consumers often create or exchange data on social networking sites, some of which are inaccurate and have no real impact. It is difficult to use algorithms to classify written works as misleading or ignorant. Even experts in this field need to consider several factors before determining the accuracy of the subject. We recommend using the ML integration method to categorize automatic news articles for this project. Our research explores various language features that can be used to distinguish between artificial and real content. Use these functions to train and test various ML algorithms on a real database. Our proposed approach to student integration outperformed individual learning in the evaluation process.