In this work we aim to illustrate some mathematical methods recently appeared in the scientific literature to detect fake news. The problem of fake news is an increasingly present topic in our society, from public debate to scientific research. The number of fake news produced is constantly increasing especially for the advantages of those who spread them. In fact, emotionally compelling news, in line with our thoughts, capture our attention, and lead to clicks and views, in the hope of attracting advertising. Understanding whether a news is false or not is not an easy problem to solve, given the large amount of data present on the internet. The detection mechanism should predict the information very quickly in order to stop the spread of fake news. This work is a review of four methods to detect fake news recently appeared in the literature [22, 33, 39, 47]. Different methodologies are observed among the various methods: statistical approach, artificial neural network, artificial intelligence and text approach. Furthermore, some results are shown.
A Short Review of Some Mathematical Methods to Detect Fake News
