Linguistic Cues to Deception and Perceived Deception in Interview Dialogues

By Sarah Ita Levitan, Angel Maredia, Julia Hirschberg. 2018

64 citations recorded by the source corpus.

We explore deception detection in interview dialogues. We analyze a set of linguistic features in both truthful and deceptive responses to interview questions. We also study the perception of deception, identifying characteristics of statements that are perceived as truthful or deceptive by interviewers. Our analysis show significant differences between truthful and deceptive question responses, as well as variations in deception patterns across gender and native language. This analysis motivated our selection of features for machine learning experiments aimed at classifying globally deceptive speech. Our best classification performance is 72.74% F1-Score (about 17% better than human performance), which is achieved using a combination of linguistic features and individual traits.

Subfields: Artificial Intelligence, Social Psychology, Natural Language Processing

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Citations in the corpus

Alignment of Language Agents (2021, background): “Detecting deception from human-generated text has been studied by e.g. Fornaciari and Poesio (2013), Pérez-Rosas et al. (2015) and Levitan et al. (2018).”