FAKE NEWS DETECTION

Abstract

The Internet is one of among the greatest inventions of the world and there are millions of individuals who utilize it. These persons employ it in various ways, as listed below: There are various social networks that are available for use among such users. Often they can be just ordinaries who decide to make a post or share the news on the internet. Such platforms offer no means of confirming any users or the content they post. Therefore, some of the users attempt to indulge in active dissemination of fake news through the platforms. This fake news can aimed at an individual, a community, a company or a political party. It becomes virtually impossible for a human being to follow all the fake news. So, currently, there exists the need for automatic classification of fake news using machine learning classifiers. My description of machine learning classifiers such as passive agressive classifiers and algorithm such as K-Nearest Neighbor, Support vector machine(SVM) is used for detecting fake news is described in this systematic literature review. KEYWORD: Fake News Dissemination, Social Networks, Automatic Classification, Machine Learning Classifiers, Passive Aggressive Classifiers, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Systematic Literature Review, Challenges in Fake News Detection.