Fake news are false and sometimes sensationalist information presented as fact and they often spread very fast on the internet via social networks like Facebook or Twitter. A possibility to identify such fake news may diminish the impact they can have. For this purpose fake news detection can be used. The term fake news detection describes the process of returning a label denoting whether a given input consists of fake news or authentic news. In this work we propose two main contributions: The first contribution is a labeled dataset of Twitter Tweets containing fake news and authentic news. Secondly we propose a web tool, which can be used to identify fake news and verify authentic Twitter Tweets based on machine learning algorithms and Twitter meta data.
19.10.17 - 10:15