TY - JOUR
T1 - Automating Linguistics-Based Cues for detecting deception in text-based asynchronous computer-mediated communication
AU - Zhou, Lina
AU - Burgoon, Judee K.
AU - Nunamaker, Jay F.
AU - Twitchell, Doug
N1 - Funding Information:
This research was partially supported by funding from the U.S. Air Force Office of Scientific Research under the U.S. Department of Defense University Research Initiative (grant #F49620-01-1-0394). The views, opinions, and/or findings in this report are those of the authors and should not be construed as an official Department of Defense position, policy, or decision.
PY - 2004/1
Y1 - 2004/1
N2 - 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 non-immediacy. 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.
AB - 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 non-immediacy. 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.
KW - Computer-mediated communication
KW - Deception
KW - Deception detection
KW - Linguistics based cue
KW - Natural language processing
UR - http://www.scopus.com/inward/record.url?scp=3843099453&partnerID=8YFLogxK
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U2 - 10.1023/B:GRUP.0000011944.62889.6f
DO - 10.1023/B:GRUP.0000011944.62889.6f
M3 - Article
AN - SCOPUS:3843099453
SN - 0926-2644
VL - 13
SP - 81
EP - 106
JO - Group Decision and Negotiation
JF - Group Decision and Negotiation
IS - 1
ER -