Mama Edha at SemEval-2017 Task 8: Stance Classification with CNN and Rules
Marianela García Lozano, Hanna Lilja, Edward Tjörnhammar, Maja Karasalo · 2017
For the competition SemEval-2017 we investigated the possibility of performing stance classification (support, deny, query or comment) for messages in Twitter conversation threads related to rumours.Stance classification is interesting since it can provide a basis for rumour veracity assessment.Our ensemble classification approach of combining convolutional neural networks with both automatic rule mining and manually written rules achieved a final accuracy of 74.9% on the competition's test data set for Task 8A.To improve classification we also experimented with data relabeling and using the grammatical structure of the tweet contents for classification.