Abstract
Social media platforms are rich sources of opinionated content. Stance detection allows the automatic extraction of users’ opinions on various topics from such content. We focus on zero-shot stance detection, where the model’s success relies on (a) having knowledge about the target topic; and (b) learning general reasoning strategies that can be employed for new topics. We present Stance Reasoner, an approach to zero-shot stance detection on social media that leverages explicit reasoning over background knowledge to guide the model’s inference about the document’s stance on a target. Specifically, our method uses a pre-trained language model as a source of world knowledge, with the chain-of-thought in-context learning approach to generate intermediate reasoning steps. Stance Reasoner outperforms the current state-of-the-art models on 3 Twitter datasets, including fully supervised models. It can better generalize across targets, while at the same time providing explicit and interpretable explanations for its predictions.- Anthology ID:
- 2024.lrec-main.1326
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 15257–15272
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.1326
- DOI:
- Cite (ACL):
- Maksym Taranukhin, Vered Shwartz, and Evangelos Milios. 2024. Stance Reasoner: Zero-Shot Stance Detection on Social Media with Explicit Reasoning. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 15257–15272, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Stance Reasoner: Zero-Shot Stance Detection on Social Media with Explicit Reasoning (Taranukhin et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2024.lrec-main.1326.pdf