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.
In follow-up work, REF developed ClaimRank, which can mimic the claim selection strategies for each and any of the nine fact-checking organizations, as well as for the union of them all.
ClaimRank: Detecting Check-Worthy Claims in Arabic and English
NAACL-2018
Computer Science