Stance and Sentiment in Czech

Sentiment analysis is a wide area with great potential and many research directions. One direction is stance detection, which is somewhat similar to sentiment analysis. We supplement stance detection dataset with sentiment annotation and explore the similarities of these tasks. We show that stance detection and sentiment analysis can be mutually beneficial by using gold label for one task as features for the other task. We analysed the presence of target entities for stance detection in the dataset. We outperform the state-of-the-art results for stance detection in Czech and set new state-of-the-art results for the newly created sentiment analysis part of the extended dataset.