Abstract
Social media posts often contain questions, but many of the questions are rhetorical and do not seek information. Our work studies the problem of distinguishing rhetorical and information-seeking questions on Twitter. Most work has focused on features of the question itself, but we hypothesize that the prior context plays a role too. This paper introduces a new dataset containing questions in tweets paired with their prior tweets to provide context. We create classification models to assess the difficulty of distinguishing rhetorical and information-seeking questions, and experiment with different properties of the prior context. Our results show that the prior tweet and topic features can improve performance on this task.- Anthology ID:
- 2020.acl-srw.41
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 306–312
- Language:
- URL:
- https://aclanthology.org/2020.acl-srw.41
- DOI:
- 10.18653/v1/2020.acl-srw.41
- Cite (ACL):
- Yuan Zhuang and Ellen Riloff. 2020. Exploring the Role of Context to Distinguish Rhetorical and Information-Seeking Questions. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pages 306–312, Online. Association for Computational Linguistics.
- Cite (Informal):
- Exploring the Role of Context to Distinguish Rhetorical and Information-Seeking Questions (Zhuang & Riloff, ACL 2020)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2020.acl-srw.41.pdf