Computer-based training for deception detection: What users want?

Jinwei Cao, Ming Lin, Amit Deokar, Judee K. Burgoon, Janna M. Crews, Mark Adkins

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

Training humans in detecting deception is as much a difficult and important problem as detecting deception itself. A computer-based deception detection training system, Agent99 Trainer, was built with a goal to train humans to understand deception and detect deception more accurately. Based on the previous studies, a newer version of this system was designed and implemented not only to overcome the limitations of the earlier system, but also to enhance it with additional useful features. In this paper, we present a usability study to test the design of this system from a users' perspective. The findings of this study, based on quantitative and qualitative data, demonstrate good usability of the training system, along with providing a better understanding of what users want from such a deception detection training system.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsHsinchun Chen, Daniel D. Zeng, Reagan Moore, John Leavitt
PublisherSpringer-Verlag
Pages163-175
Number of pages13
ISBN (Electronic)9783540221258
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3073
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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