Abstract
Our society is struggling with an unprecedented amount of falsehoods, hyperboles, and half-truths. Politicians and organizations repeatedly make the same false claims. Fake news floods the cyberspace and even allegedly influenced the 2016 election. In fighting false information, the number of active fact-checking organizations has grown from 44 in 2014 to 114 in early 2017. 1 Fact-checkers vet claims by investigating relevant data and documents and publish their verdicts. For instance, PolitiFact.com, one of the earliest and most popular fact-checking projects, gives factual claims truthfulness ratings such as True, Mostly True, Half true, Mostly False, False, and even "Pants on Fire". In the U.S., the election year made fact-checking a part of household terminology. For example, during the first presidential debate on September 26, 2016, NPR.org's live fact-checking website drew 7.4 million page views and delivered its biggest traffic day ever.
- F. Arslan. Detecting real-time check-worthy factual claims in tweets related to U.S. politics. Master's thesis, University of Texas at Arlington, 2015.Google Scholar
- FullFact.org. The State of Automated Factchecking. Full Fact, August, 2016. https://fullfact.org/blog/2016/aug/automated-factchecking/.Google Scholar
- N. Hassan, B. Adair, J. T. Hamilton, C. Li, M. Tremayne, J. Yang, and C. Yu. The quest to automate fact-checking. In Computation+Journalism Symposium, 2015.Google Scholar
- N. Hassan, C. Li, and M. Tremayne. Detecting check-worthy factual claims in presidential debates. In CIKM, pages 1835--1838, 2015. Google ScholarDigital Library
- N. Hassan, M. Tremayne, F. Arslan, and C. Li. Comparing automated factual claim detection against judgments of journalism organizations. In Computation+Journalism Symposium, 2016.Google Scholar
- M. Heilman and N. A. Smith. Question generation via overgenerating transformations and ranking. Technical report, CMU-LTI-09-013, Carnegie Mellon University, 2009.Google Scholar
- M. Joseph. Speaker identification in live events using Twitter. Master's thesis, University of Texas at Arlington, 2015.Google Scholar
- V. Rus, M. C. Lintean, R. Banjade, N. B. Niraula, and D. Stefanescu. Semilar: The semantic similarity toolkit. In ACL, 2013.Google Scholar
Index Terms
- ClaimBuster: the first-ever end-to-end fact-checking system
Comments