Abstract
We study the problem of performing automatic stance classification on social media with neural architectures such as BERT. Although these architectures deliver impressive results, their level is not yet comparable to the one of humans and they might produce errors that have a significant impact on the downstream task (e.g., fact-checking). To improve the performance, we present a new neural architecture where the input also includes automatically generated negated perspectives over a given claim. The model is jointly learned to make simultaneously multiple predictions, which can be used either to improve the classification of the original perspective or to filter out doubtful predictions. In the first case, we propose a weakly supervised method for combining the predictions into a final one. In the second case, we show that using the confidence scores to remove doubtful predictions allows our method to achieve human-like performance over the retained information, which is still a sizable part of the original input.- Anthology ID:
- 2021.emnlp-main.547
- Volume:
- Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Month:
- November
- Year:
- 2021
- Address:
- Online and Punta Cana, Dominican Republic
- Editors:
- Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 6831–6843
- Language:
- URL:
- https://aclanthology.org/2021.emnlp-main.547
- DOI:
- 10.18653/v1/2021.emnlp-main.547
- Cite (ACL):
- Song Yang and Jacopo Urbani. 2021. Tribrid: Stance Classification with Neural Inconsistency Detection. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 6831–6843, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- Tribrid: Stance Classification with Neural Inconsistency Detection (Yang & Urbani, EMNLP 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2021.emnlp-main.547.pdf
- Code
- karmaresearch/tribrid
- Data
- Perspectrum