Abstract
Studies based on mean accuracy of a group of subjects suggest that most observers do no better than chance in detecting the lies of others. We argue that a case-by-case methodology, like that used in polygraphy studies may be more useful. Three behavioral measures (two kinds of smiles and pitch) were used to make predictions about the lying or truthfulness of each of 31 subjects. A case-by-case analysis of the hits and misses achieved in this way yielded an over-all accuracy of 86%. The effect on lie detection accuracy of individual differences in the use and control of different behavioral channels is discussed.
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Paul Ekman's work is supported by a Research Scientist Award from the National Institute of Mental Health (MH 06092).
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Ekman, P., O'Sullivan, M., Friesen, W.V. et al. Invited article: Face, voice, and body in detecting deceit. J Nonverbal Behav 15, 125–135 (1991). https://doi.org/10.1007/BF00998267
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DOI: https://doi.org/10.1007/BF00998267