Mining Bodily Cues to Deception

Ronald Poppe*, Sophie van der Zee, Paul J. Taylor, Ross J. Anderson, Remco C. Veltkamp

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
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Abstract

A significant body of research has investigated potential correlates of deception and bodily behavior. The vast majority of these studies consider discrete, subjectively coded bodily movements such as specific hand or head gestures. Such studies fail to consider quantitative aspects of body movement such as the precise movement direction, magnitude and timing. In this paper, we employ an innovative data mining approach to systematically study bodily correlates of deception. We re-analyze motion capture data from a previously published deception study, and experiment with different data coding options. We report how deception detection rates are affected by variables such as body part, the coding of the pose and movement, the length of the observation, and the amount of measurement noise. Our results demonstrate the feasibility of a data mining approach, with detection rates above 65%, significantly outperforming human judgement (52.80%). Owing to the systematic analysis, our analyses allow for an understanding of the importance of various coding factor. Moreover, we can reconcile seemingly discrepant findings in previous research. Our approach highlights the merits of data-driven research to support the validation and development of deception theory.

Original languageEnglish
Pages (from-to)137-159
Number of pages23
JournalJournal of Nonverbal Behavior
Volume48
Issue number1
DOIs
Publication statusE-pub ahead of print - 16 Jan 2024

Bibliographical note

Publisher Copyright: © 2024, The Author(s).

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