Automating Linguistics-Based Cues for Detecting Deception in Text-Based Asynchronous Computer-Mediated Communications
Lina Zhou (),
Judee K. Burgoon (),
Jay F. Nunamaker () and
Doug Twitchell ()
Additional contact information
Lina Zhou: University of Maryland
Judee K. Burgoon: University of Arizona
Jay F. Nunamaker: University of Arizona
Doug Twitchell: University of Arizona
Group Decision and Negotiation, 2004, vol. 13, issue 1, No 6, 106 pages
Abstract:
Abstract 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.
Keywords: deception; deception detection; linguistics based cue; computer-mediated communication; natural language processing (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (15)
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DOI: 10.1023/B:GRUP.0000011944.62889.6f
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