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.
Cite
CITATION STYLE
Kartal, Y. S., & Kutlu, M. (2020). TrClaim-19: The First Collection for Turkish Check-Worthy Claim Detection with Annotator Rationales. In CoNLL 2020 - 24th Conference on Computational Natural Language Learning, Proceedings of the Conference (pp. 386–395). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2020.conll-1.31
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