Analysis of Various Machine Learning Methods of Fake News Detection

Abstract

Fake news detection is becoming more and more critical with time. This research article surveys the existing methods for fake news detection. Various machine learning algorithms have also been compared based on their effectiveness and efficiency in classifying the fake news in terms of accuracy/F1 score and computational time. The author has attempted to give a comprehensive analysis of six machine learning algorithms in classifying fake news using the bag of words approach. It also analyses the relationship between the frequencies of particular type of words with fake news.