@inbook{4303a4452cd7430192d4f93b1ab0e7ac,
title = "Training professionals to detect deception",
abstract = "Humans are not very good at detecting deception in normal communication. One possible remedy for improving detection accuracy is to educate people about various indicators of deception and then train them to spot these indicators when they are used in normal communication. This paper reports on one such training effort involving over 100 military officers. Participants received training on deception detection generally, on specific indicators, and on heuristics. They completed pre- and post-tests on their knowledge in these areas and on their ability to detect deception. Detection accuracy was measured by asking participants to judge if behavior in a video, on an audiotape, or in a text passage was deceptive or honest. Trained individuals outperformed those who did not receive training on the knowledge tests, but there were no differences between the groups in detection accuracy.",
author = "George, {Joey F.} and Biros, {David P.} and Burgoon, {Judee K.} and Nunamaker, {Jay F.}",
year = "2003",
doi = "10.1007/3-540-44853-5_31",
language = "English (US)",
isbn = "354040189X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "366--370",
editor = "Hsinchun Chen and Zeng, {Daniel D.} and Therani Madhusudan and Richard Miranda and Jenny Schroeder and Chris Demchak",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}