Understanding of Fake News Dissemination on Social Media by Comparing IPS, MF, NCF and BPR

Abstract

In these years, there are dramatic development in the fake news detection field. The spread of fake news influences people's daily life, reduces the value of real news, and sometimes blemishes people's images. This phenomenon has raised our attention, so we are interested in making some effort to reduce the negative impact of it. We focus on the point that whether the users will spread the news if all the news is read by the users (from the causal inference aspect). We use negative sampling to avoid the problem that there is only positive feedback in the real-world dataset. Then we compare IPS, MF, NCF and BPR to discover the best to help us to solve this question.