Stance Classification and Rumour Verification on Twitter

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.   

Project Poster: 

Project Members: 

Gökçe Uludoğan

Project Advisor: 

Arzucan Özgür

Project Status: 

Project Year: 

  • Spring

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