Group Decision and Negotiation

, Volume 13, Issue 1, pp 81–106 | Cite as

Automating Linguistics-Based Cues for Detecting Deception in Text-Based Asynchronous Computer-Mediated Communications

  • Lina Zhou
  • Judee K. Burgoon
  • Jay F. Nunamaker
  • Doug Twitchell


The detection of deception is a promising but challenging task. A systematic discussion of automated Linguistics Based Cues (LBC) to deception has rarely been touched before. The experiment studied the effectiveness of automated LBC in the context of text-based asynchronous computer mediated communication (TA-CMC). Twenty-seven cues either extracted from the prior research or created for this study were clustered into nine linguistics constructs: quantity, diversity, complexity, specificity, expressivity, informality, affect, uncertainty, and nonimmediacy. A test of the selected LBC in a simulated TA-CMC experiment showed that: (1) a systematic analysis of linguistic information could be useful in the detection of deception; (2) some existing LBC were effective as expected, while some others turned out in the opposite direction to the prediction of the prior research; and (3) some newly discovered linguistic constructs and their component LBC were helpful in differentiating deception from truth.

deception deception detection linguistics based cue computer-mediated communication natural language processing 


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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Lina Zhou
    • 1
  • Judee K. Burgoon
    • 2
  • Jay F. Nunamaker
    • 2
  • Doug Twitchell
    • 2
  1. 1.Department of Information SystemsUniversity of MarylandBaltimore CountyUSA E-mail
  2. 2.Center for the Management of InformationUniversity of ArizonaTucsonUSA E-mail

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