Detecting deception using comparable truth baselines

Dataset

Description

Baselining – comparing the statements of interest to a known truthful statement by the same individual – has been suggested to improve lie detection accuracy. 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. Exposure to a truthful baseline statement resulted in a lower truth accuracy but no difference in lie accuracy.
Date made available20 Jan 2022
PublisherDataverseNL

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