TY - JOUR
T1 - The linguistic correlates of conversational deception
T2 - Comparing natural language processing technologies
AU - Duran, Nicholas D.
AU - Hall, Charles
AU - McCarthy, Philip M.
AU - McNamara, Danielle S.
N1 - Funding Information:
This research was supported in part by the Institute for Education Sciences (IES R305G020018-02, IES R305a080589), Department of Defense/CIFA (H9C104-07-C0019), and a National Science Foundation Graduate Research Fellowship awarded (to N.D.D.). The views expressed in this paper do not necessarily reflect the views of the Institute for Education Sciences, Department of Defense, or National Science Foundation. The authors thank Jeff Hancock for providing us with the conversational transcripts used in this study. The authors also acknowledge the contributions to this project made by Arthur Graesser, Zhiqiang Cai, and Joe Weintraub.
PY - 2010/7
Y1 - 2010/7
N2 - The words people use and the way they use them can reveal a great deal about their mental states when they attempt to deceive. The challenge for researchers is how to reliably distinguish the linguistic features that characterize these hidden states. In this study, we use a natural language processing tool called Coh-Metrix to evaluate deceptive and truthful conversations that occur within a context of computer-mediated communication. Coh-Metrix is unique in that it tracks linguistic features based on cognitive and social factors that are hypothesized to influence deception. The results from Coh-Metrix are compared to linguistic features reported in previous independent research, which used a natural language processing tool called Linguistic Inquiry and Word Count. The comparison reveals converging and contrasting alignment for several linguistic features and establishes new insights on deceptive language and its use in conversation.
AB - The words people use and the way they use them can reveal a great deal about their mental states when they attempt to deceive. The challenge for researchers is how to reliably distinguish the linguistic features that characterize these hidden states. In this study, we use a natural language processing tool called Coh-Metrix to evaluate deceptive and truthful conversations that occur within a context of computer-mediated communication. Coh-Metrix is unique in that it tracks linguistic features based on cognitive and social factors that are hypothesized to influence deception. The results from Coh-Metrix are compared to linguistic features reported in previous independent research, which used a natural language processing tool called Linguistic Inquiry and Word Count. The comparison reveals converging and contrasting alignment for several linguistic features and establishes new insights on deceptive language and its use in conversation.
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U2 - 10.1017/S0142716410000068
DO - 10.1017/S0142716410000068
M3 - Article
AN - SCOPUS:77957264233
SN - 0142-7164
VL - 31
SP - 439
EP - 462
JO - Applied Psycholinguistics
JF - Applied Psycholinguistics
IS - 3
ER -