Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking

Hannah Rashkin, Eunsol Choi, Jin Yea Jang, Svitlana Volkova, Yejin Choi


Abstract
We present an analytic study on the language of news media in the context of political fact-checking and fake news detection. We compare the language of real news with that of satire, hoaxes, and propaganda to find linguistic characteristics of untrustworthy text. To probe the feasibility of automatic political fact-checking, we also present a case study based on PolitiFact.com using their factuality judgments on a 6-point scale. Experiments show that while media fact-checking remains to be an open research question, stylistic cues can help determine the truthfulness of text.
Anthology ID:
D17-1317
Volume:
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Martha Palmer, Rebecca Hwa, Sebastian Riedel
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
2931–2937
Language:
URL:
https://aclanthology.org/D17-1317
DOI:
10.18653/v1/D17-1317
Bibkey:
Cite (ACL):
Hannah Rashkin, Eunsol Choi, Jin Yea Jang, Svitlana Volkova, and Yejin Choi. 2017. Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2931–2937, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking (Rashkin et al., EMNLP 2017)
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PDF:
https://preview.aclanthology.org/naacl24-info/D17-1317.pdf
Video:
 https://preview.aclanthology.org/naacl24-info/D17-1317.mp4