A comparative analysis of machine learning algorithms for fake news detection

With the increase in the use of social media platforms like Facebook, Twitter, etc. news spread rapidly among millions of users within a very short span of time. The spread of fake news has far-reaching consequences like the creation of biased opinions to swaying election outcomes for the benefit of certain candidates. In this paper, aim is to perform binary classification of various news articles available online with the help of concepts pertaining to Artificial Intelligence, Natural Language Processing and Machine Learning. We aim to provide the user with the ability to classify the news as fake or real. Fake news detection is an emerging research area which is ahead big interest. It faces however some challenges due to the limited resources such as datasets and processing and analysing techniques