Feature analysis of fake news: improving fake news detection in social media

Fake news is a threat to society, and its spread can have real-world consequences in many situations. For example, attackers have weaponised fake news to influence user opinion by causing users to emotionally react to fake news. On the other hand, fake news can also be a threat to national democracy. Therefore, we investigate textual sentiment, visual sentiment, behavioural and metadata features that entice users, using a dataset of posts from Reddit and another from Twitter, that were already categorised into the labels of fake news and real news. First, we extract features, such as visual sentiment, textual sentiment, behavioural reactions, and metadata, and then analyse various features for fake news prediction. We then run a machine learning experiment to classify posts that help improve fake news detection in social media.