Detecting deception through linguistic analysis

Judee K Burgoon, J. P. Blair, Tiantian Qin, Jay F Nunamaker

Research output: Contribution to journalArticle

66 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)91-101
Number of pages11
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2665
StatePublished - 2003

Fingerprint

Deception
Aptitude
Linguistics
Language
Theft
Preliminary Test
Cues
Experiments
Likely
Predict
Demonstrate
Experiment
Text
Truth

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

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