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Data · dataset · 2022

Detecting deception using comparable truth baselines

Listed in IISH Dataverse and ODISSEI Portal — shown once because both records carry DOI 10.34894/y2taj9

Baselining – comparing the statements of interest to a known truthful statement by the same individual – has been suggested to improve lie detection accuracy.

Description

A potential downside of baselining is that it might influence the characteristics of a subsequent statement, as was shown in previous studies. In our first experiment we examined this claim but found no evidence that a truthful baseline influenced the characteristics of a subsequent statement.

Next, we investigated whether using a truthful baseline statement as a within-subject comparison would improve lie detection performance by investigating verbal cues (Experiment 1) and intuitive judgements of human judges (Experiment 2). Our exploratory analyses showed that truth tellers included more auditory and temporal details in their target statement than in their baseline than liars. Observers did not identify this verbal pattern.

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Exposure to a truthful baseline statement resulted in a lower truth accuracy but no difference in lie accuracy.

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Stated by source
Social Sciences · Social Sciences
Provenance · 2 source records, 10 field assertions
SourceKeyLast seenRaw
IISH Dataversedoi:10.34894/Y2TAJ913 d agoJSON v1
ODISSEI Portaldoi:10.34894/Y2TAJ99 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].dataverse_subject:social-sciencessource · portal odissei nlconnector:portal_odissei_nl@1.0.0/subjects
concepts[field].local:field:social-sciencemapping · portal odissei nlconnector:portal_odissei_nl@1.0.0/subjects
concepts[field].local:field:social-sciencemapping · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
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