Abstract
Massive misinformation spread over Internet has many negative impacts on our lives. While spreading a claim is easy, investigating its veracity is hard and time consuming, Therefore, we urgently need systems to help human fact-checkers. However, available data resources to develop effective systems are limited and the vast majority of them is for English. In this work, we introduce TrClaim-19, which is the very first labeled dataset for Turkish check-worthy claims. TrClaim-19 consists of labeled 2287 Turkish tweets with annotator rationales, enabling us to better understand the characteristics of check-worthy claims. The rationales we collected suggest that claims’ topics and their possible negative impacts are the main factors affecting their check-worthiness.- Anthology ID:
- 2020.conll-1.31
- Volume:
- Proceedings of the 24th Conference on Computational Natural Language Learning
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Raquel Fernández, Tal Linzen
- Venue:
- CoNLL
- SIG:
- SIGNLL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 386–395
- Language:
- URL:
- https://aclanthology.org/2020.conll-1.31
- DOI:
- 10.18653/v1/2020.conll-1.31
- Cite (ACL):
- Yavuz Selim Kartal and Mucahid Kutlu. 2020. TrClaim-19: The First Collection for Turkish Check-Worthy Claim Detection with Annotator Rationales. In Proceedings of the 24th Conference on Computational Natural Language Learning, pages 386–395, Online. Association for Computational Linguistics.
- Cite (Informal):
- TrClaim-19: The First Collection for Turkish Check-Worthy Claim Detection with Annotator Rationales (Kartal & Kutlu, CoNLL 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.conll-1.31.pdf