An analysis of text-based deception detection tools

Christie M. Fuller, David P. Biros, Douglas P. Twitchell, Judee K. Burgoon, Mark Adkins

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

The quality of information can be degraded when individuals attempt to deceive others through information manipulation. This can be very influential in a text-based domain. In recent years, tools have been developed that, while not initially designed for this domain, have been adapted successfully for use in identifying deception in text-based communication. These text analysis tools, which utilize features such as parsing and categorizing, are emerging as accurate tools to identify cues that may be useful in distinguishing deceptive from truthful communications. These deception detection tools have been applied to problems such as security screening, criminal incident statements, and evaluation of online communication patterns. This paper provides a comparative analysis of the features and capabilities of two of the more promising tools and identifies how their use might fit within existing theoretical constructs.

Original languageEnglish (US)
Title of host publicationAssociation for Information Systems - 12th Americas Conference On Information Systems, AMCIS 2006
Pages3453-3460
Number of pages8
StatePublished - Dec 1 2006
Event12th Americas Conference on Information Systems, AMCIS 2006 - Acapulco, Mexico
Duration: Aug 4 2006Aug 6 2006

Publication series

NameAssociation for Information Systems - 12th Americas Conference On Information Systems, AMCIS 2006
Volume6

Other

Other12th Americas Conference on Information Systems, AMCIS 2006
CountryMexico
CityAcapulco
Period8/4/068/6/06

Keywords

  • Cues
  • Deception
  • Deception detection
  • Linguistic analysis
  • Text

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Networks and Communications
  • Library and Information Sciences
  • Information Systems

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