five

The Impact of Model Statements on Verbal Differences between Truth and Lies when using a Comparable Truthful Baseline

收藏
DataCite Commons2026-03-25 更新2026-04-25 收录
下载链接:
https://dataverse.nl/citation?persistentId=doi:10.34894/GI4MVT
下载链接
链接失效反馈
官方服务:
资源简介:
Baselining is a deception detection technique that compares a statement of interest to a baseline. This study focused on verbal baselining: it examined differences in detailedness between the baseline and the statement of interest as a cue to deception. Across two experiments, participants watched two crime videos and provided two statements: one truthful baseline and one statement of interest, which was either truthful or deceptive depending on the condition. Half of the participants were shown a model statement before giving their responses. In Experiment 1 (using written statements), both the model statement and the baseline independently improved truth/lie discrimination. In Experiment 2 (using spoken statements), however, these effects were not replicated. Importantly, combining a model statement with baselining did not further improve truth/lie discrimination in either experiment. These findings underscore the complexity of verbal lie detection and highlight the need to better understand when and how baselining techniques are most effective.
提供机构:
DataverseNL
创建时间:
2025-07-07
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作