Tohoku at SemEval-2016 task 6: Feature-based model versus convolutional neural network for stance detection

Abstract

In this paper, we compare feature-based and Neural Network-based approaches on the supervised stance classification task for tweets in SemEval-2016 Task 6 Subtask A (Mohammad et al., 2016). In the feature-based approach, we use external resources such as lexicons and crawled texts. The Neural Network based approach employs Convolutional Neural Network (CNN). Our results show that the feature-based model outperformed the CNN model on the test data although the CNN model was better than the feature-based model in the cross validation on the training data.