Various Approaches for Fake News Detection

Abstract

Traditional media has been changed via way of means of online network and has end up as main platform for spreading fake news. Access to the Internethas led to create faster and easier ways of communication through social media instead of traditional news sources. Fake news can be spread easily from unverified sources which may mislead the readers. Detecting fake news was accomplished manually in the past which was tedious, but now there are many automated methods which uses machine learning techniques and other related fields which reduces human effort. This paper provides comparison and evaluation of various machine learning techniques in different social media platforms. These techniques include classification algorithms like Naive Bayes and other deep learning algorithms like CNN, RNN, LSTM.