Fact Checking or Psycholinguistics: How to Distinguish Fake and True Claims?

Aleksander Wawer, Grzegorz Wojdyga, Justyna Sarzyńska-Wawer


Abstract
The goal of our paper is to compare psycholinguistic text features with fact checking approaches to distinguish lies from true statements. We examine both methods using data from a large ongoing study on deception and deception detection covering a mixture of factual and opinionated topics that polarize public opinion. We conclude that fact checking approaches based on Wikipedia are too limited for this task, as only a few percent of sentences from our study has enough evidence to become supported or refuted. Psycholinguistic features turn out to outperform both fact checking and human baselines, but the accuracy is not high. Overall, it appears that deception detection applicable to less-than-obvious topics is a difficult task and a problem to be solved.
Anthology ID:
D19-6602
Volume:
Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER)
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
James Thorne, Andreas Vlachos, Oana Cocarascu, Christos Christodoulopoulos, Arpit Mittal
Venue:
WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
7–12
Language:
URL:
https://aclanthology.org/D19-6602
DOI:
10.18653/v1/D19-6602
Bibkey:
Cite (ACL):
Aleksander Wawer, Grzegorz Wojdyga, and Justyna Sarzyńska-Wawer. 2019. Fact Checking or Psycholinguistics: How to Distinguish Fake and True Claims?. In Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER), pages 7–12, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Fact Checking or Psycholinguistics: How to Distinguish Fake and True Claims? (Wawer et al., 2019)
Copy Citation:
PDF:
https://aclanthology.org/D19-6602.pdf