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Expertise in Deception Detection Involves Actively Prompting Diagnostic Information Rather Than Passive Behavioral Observation
- Levine, Timothy Roland;
- Clare, David Daniel;
- Blair, J. Pete;
- McCornack, Steve;
- Morrison, Kelly;
- ... Park, Hee Sun
WEB OF SCIENCE
23SCOPUS
36초록
In a proof-of-concept study, an expert obtained 100% deception-detection accuracy over 33 interviews. Tapes of the interactions were shown to N=136 students who obtained 79.1% accuracy (Mdn=83.3%, mode=100%). The findings were replicated in a second experiment with 5 different experts who collectively conducted 89 interviews. The new experts were 97.8% accurate in cheating detection and 95.5% accurate at detecting who cheated. A sample of N=34 students watched a random sample of 36 expert interviews and obtained 93.6% accuracy. The data suggest that experts can accurately distinguish truths from lies when they are allowed to actively question a potential liar, and nonexperts can obtain high accuracy when viewing expertly questioned senders.
키워드
- 제목
- Expertise in Deception Detection Involves Actively Prompting Diagnostic Information Rather Than Passive Behavioral Observation
- 저자
- Levine, Timothy Roland; Clare, David Daniel; Blair, J. Pete; McCornack, Steve; Morrison, Kelly; Park, Hee Sun
- 발행일
- 2014-10
- 유형
- Article
- 권
- 40
- 호
- 4
- 페이지
- 442 ~ 462