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Automated insights: verbal cues to deception in real-life high-stakes lies

Authors: Sarah M. McQuaid; Michael Woodworth; Erin L. Hutton; Stephen Porter; Leanne ten Brinke;

Automated insights: verbal cues to deception in real-life high-stakes lies

Abstract

This study differentiated between the language of deceptive and genuine pleaders who were pleading for the return of a missing loved one during a televised press conference. The Wmatrix linguistic analysis tool was used to examine the language of 78 pleaders. Approximately half (n = 35) of these individuals were deceptive and were responsible for the disappearance. Transcripts of the pleas were analyzed for various linguistic cues, and a separate analysis was conducted across gender. Results revealed that deceptive pleaders used the word ‘they,’ singular indefinite pronouns (e.g., ‘anybody,’ ‘somebody’), and exclusivizers/particularizers (e.g., ‘just’) significantly more than genuine pleaders, while genuine pleaders used more temporal words (e.g., ‘days,’ ‘weeks’), and the word ‘we’ more frequently in their pleas. Specific gender differences were also revealed across credible and deceptive pleaders. Our analysis of linguistic differences across pleader veracity provides an enhanced understanding of the ve...

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    16
    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Average
Top 10%
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