ClaimRank: Detecting Check-Worthy Claims in Arabic and English

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Abstract

We present ClaimRank, an online system for detecting check-worthy claims. While originally trained on political debates, the system can work for any kind of text, e.g., interviews or regular news articles. Its aim is to facilitate manual fact-checking efforts by prioritizing the claims that fact-checkers should consider first. ClaimRank supports both Arabic and English, it is trained on actual annotations from nine reputable fact-checking organizations (PolitiFact, FactCheck, ABC, CNN, NPR, NYT, Chicago Tribune, The Guardian, and Washington Post), and thus it can mimic the claim selection strategies for each and any of them, as well as for the union of them all.

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APA

Jaradat, I., Gencheva, P., Barrón-Cedeño, A., Màrquez, L., & Nakov, P. (2018). ClaimRank: Detecting Check-Worthy Claims in Arabic and English. In NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Demonstrations Session (pp. 26–30). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/n18-5006

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