Deception detection through automatic, unobtrusive analysis of nonverbal behavior

Thomas O. Meservy; Matthew L. Jensen; John Kruse; Judee K. Burgoon; Jay F. Nunamaker; Douglas P. Twitchell; Gabriel Tsechpenakis; Dimitris N. Metaxas

doi:10.1109/MIS.2005.85

Deception detection through automatic, unobtrusive analysis of nonverbal behavior

Thomas O. Meservy
, Matthew L. Jensen
, John Kruse
, Judee K. Burgoon
, Jay F. Nunamaker
, Douglas P. Twitchell
, Gabriel Tsechpenakis
, Dimitris N. Metaxas

Information Technology and Supply Chain Management Department

University of Arizona
IEEE
International Communication Association
National Communication Association
Society for Experimental Social Psychology
Society for Personality and Social Psychology
Rutgers - The State University of New Jersey, New Brunswick
TCG (Greek Technical Chamber
HAMEE (Hellenic Association of Mechanical and Electrical Engineers
Division of Comrjuter and Information Sciences

Research output: Contribution to journal › Review article › peer-review

97 Scopus citations

Abstract

An approach for deception detection through automatic, unobtrusive analysis of nonverbal behavior was described. An automated unobtrusive system identifies behavioral patterns that indicate deception from nonverbal behavioral cues and classifies deception and truth more accurately than many humans. Automated systems can draw upon a wide variety of potential behavioral indicators of deception. It is expected that the automated systems might become reliable enough to replace humans in certain circumstances, thus allowing a redistribution of human assets.

Original language	English
Pages (from-to)	36-43
Number of pages	8
Journal	IEEE Intelligent Systems
Volume	20
Issue number	5
DOIs	https://doi.org/10.1109/MIS.2005.85
State	Published - Sep 2005

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10.1109/MIS.2005.85

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abstract = "An approach for deception detection through automatic, unobtrusive analysis of nonverbal behavior was described. An automated unobtrusive system identifies behavioral patterns that indicate deception from nonverbal behavioral cues and classifies deception and truth more accurately than many humans. Automated systems can draw upon a wide variety of potential behavioral indicators of deception. It is expected that the automated systems might become reliable enough to replace humans in certain circumstances, thus allowing a redistribution of human assets.",

author = "Meservy, \{Thomas O.\} and Jensen, \{Matthew L.\} and John Kruse and Burgoon, \{Judee K.\} and Nunamaker, \{Jay F.\} and Twitchell, \{Douglas P.\} and Gabriel Tsechpenakis and Metaxas, \{Dimitris N.\}",

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AU - Meservy, Thomas O.

AU - Jensen, Matthew L.

AU - Kruse, John

AU - Burgoon, Judee K.

AU - Nunamaker, Jay F.

AU - Twitchell, Douglas P.

AU - Tsechpenakis, Gabriel

AU - Metaxas, Dimitris N.

PY - 2005/9

Y1 - 2005/9

N2 - An approach for deception detection through automatic, unobtrusive analysis of nonverbal behavior was described. An automated unobtrusive system identifies behavioral patterns that indicate deception from nonverbal behavioral cues and classifies deception and truth more accurately than many humans. Automated systems can draw upon a wide variety of potential behavioral indicators of deception. It is expected that the automated systems might become reliable enough to replace humans in certain circumstances, thus allowing a redistribution of human assets.

AB - An approach for deception detection through automatic, unobtrusive analysis of nonverbal behavior was described. An automated unobtrusive system identifies behavioral patterns that indicate deception from nonverbal behavioral cues and classifies deception and truth more accurately than many humans. Automated systems can draw upon a wide variety of potential behavioral indicators of deception. It is expected that the automated systems might become reliable enough to replace humans in certain circumstances, thus allowing a redistribution of human assets.

UR - https://www.scopus.com/pages/publications/27344451145

U2 - 10.1109/MIS.2005.85

DO - 10.1109/MIS.2005.85

M3 - Review article

AN - SCOPUS:27344451145

SN - 1541-1672

VL - 20

SP - 36

EP - 43

JO - IEEE Intelligent Systems

JF - IEEE Intelligent Systems

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ER -

Deception detection through automatic, unobtrusive analysis of nonverbal behavior

Abstract

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