Stance Classification and Rumour Verification on Twitter

As social media has become widespread, it is increasingly used as a way of gathering and conveying information about news and controversial issues. To prevent false information/rumours from spreading or verify them immediately, there is a need for rumour classification system. This work focuses on stance classification towards rumours and rumour verification on Twitter. It utilizes a deep learning model on stance classification and supervised learning models on rumour verification. The obtained accuracies are 76.54% for stance classification and 53.57% for rumour verification which is equal to the state-of-the-art model's performance.