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Abstract

Deception detection methods have advanced beyond identifying nonverbal behavior with increasing focus on content analysis of verbal behavior. Content analysis deception detection has been dominated by lexicon-based approaches. The verifiability approach is a newer method of content analysis deception detection. The purpose of this study was to compare these approaches on the same data set to assess whether lexicon-based or verifiability approach content analysis is more accurate at detecting deception. In this study, lexicon-based content analysis using the Linguistic Inquiry and Word Count (LIWC) software was conducted on accounts from a prior verifiability approach study. Separate regression models were constructed to assess honest and deceptive alibi accounts using each approach. Both the lexicon-based and verifiability models detected deception at above chance accuracy; predictive accuracy did not significantly differ between these approaches. Implications for the application of content analysis to detect deception are discussed.

Keywords

content analysis deception detection lexicon-based approach verifiability approach LIWC reality monitoring

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Deception Detection: Comparing the Lexicon-Based Approaches and Verifiability Approach

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