Detecting deception through linguistic analysis

Authors:
Judee K. Burgoon;J. P. Blair;Tiantian Qin;Jay F. Nunamaker, Jr.
Affiliations:
Center for the Management of Information, University of Arizona;Department of Criminal Justice, Michigan State University;Center for the Management of Information, University of Arizona;Center for the Management of Information, University of Arizona
Venue:
ISI'03 Proceedings of the 1st NSF/NIJ conference on Intelligence and security informatics
Year:
2003

Citing 2
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Abstract

Tools to detect deceit from language use pose a promising avenue for increasing the ability to distinguish truthful transmissions, transcripts, intercepted messages, informant reports and the like from deceptive ones. This investigation presents preliminary tests of 16 linguistic features that can be automated to return assessments of the likely truthful or deceptiveness of a piece of text. Results from a mock theft experiment demonstrate that deceivers do utilize language differently than truth tellers and that combinations of cues can improve the ability to predict which texts may contain deception.