ClaimRank: Detecting Check-Worthy Claims in Arabic and English

Israa Jaradat, Pepa Gencheva, Alberto Barrón-Cedeño, Lluís Màrquez, Preslav Nakov


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 just 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.
Anthology ID:
N18-5006
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Yang Liu, Tim Paek, Manasi Patwardhan
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
26–30
Language:
URL:
https://aclanthology.org/N18-5006
DOI:
10.18653/v1/N18-5006
Bibkey:
Cite (ACL):
Israa Jaradat, Pepa Gencheva, Alberto Barrón-Cedeño, Lluís Màrquez, and Preslav Nakov. 2018. ClaimRank: Detecting Check-Worthy Claims in Arabic and English. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pages 26–30, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
ClaimRank: Detecting Check-Worthy Claims in Arabic and English (Jaradat et al., NAACL 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/dois-2013-emnlp/N18-5006.pdf