Fake news detection using machine learning

Abstract

For some years, mostly since the rise of social media, fake news have become a society problem, in some occasion spreading more and faster than the true information. In this paper I evaluate the performance of Attention Mechanism for fake news detection on two datasets, one containing traditional online news articles and the second one news from various sources. I compare results on both dataset and the results of Attention Mechanism against LSTMs and traditional machine learning methods. It shows that Attention Mechanism does not work as well as expected. In addition, I made changes to original Attention Mechanism paper, by using word2vec embedding, that proves to works better on this particular case.