Fact Checking or Psycholinguistics: How to Distinguish Fake and True Claims?
Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER)(2019)
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.
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Key words
Fact-Checking,Topic Modeling
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