Hostname: page-component-7c8c6479df-24hb2 Total loading time: 0 Render date: 2024-03-28T09:26:29.078Z Has data issue: false hasContentIssue false

The linguistic correlates of conversational deception: Comparing natural language processing technologies

Published online by Cambridge University Press:  04 June 2010

NICHOLAS D. DURAN*
Affiliation:
University of Memphis
CHARLES HALL
Affiliation:
University of Memphis
PHILIP M. MCCARTHY
Affiliation:
University of Memphis
DANIELLE S. MCNAMARA
Affiliation:
University of Memphis
*
ADDRESS FOR CORRESPONDENCE Nicholas Duran, Department of Psychology, University of Memphis, Memphis, TN 38152. E-mail: nduran@memphis.edu

Abstract

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.

Type
Articles
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Beck, I. L., McKeown, M. G., Sinatra, G. M., & Loxterman, J. A. (1991). Revising social studies text from a text-processing perspective: Evidence of improved comprehensibility. Reading Research Quarterly, 26, 251276.CrossRefGoogle Scholar
Brown, B. (1977). Face saving and face restoration in negotiation. In Druckman, D. (Ed.), Negotiations: Social–psychological perspectives (pp. 275299). Beverly Hills, CA: Sage.Google Scholar
Buller, D. B., & Burgoon, J. K. (1996). Interpersonal deception theory. Communication Theory, 3, 203242.CrossRefGoogle Scholar
Burgoon, J., Buller, D., & Floyd, K. (2001). Does participation affect deception success? A test of the interactivity principle. Human Communications Research, 27, 503534.Google Scholar
Burgoon, J. K., Buller, D. B., Floyd, K., & Grandpre, J. (1996). Deceptive realities: Sender, receiver, and observer perspectives in deceptive conversations. Communication Research, 23, 724748.CrossRefGoogle Scholar
Carlson, J. R., George, J. F., Burgoon, J. K., Adkins, M., & White, C. H. (2004). Deception in computer-mediated communication. Group Decision and Negotiation, 13, 528.CrossRefGoogle Scholar
Charniak, E. (1997). Statistical techniques for natural language processing. AI Magazine, 18, 3344.Google Scholar
Charniak, E. (2000). A maximum-entropy-inspired parser. Paper presented at the 1st Meeting of the North American Chapter of the Association for Computational Linguistics, Seattle, WA.Google Scholar
Clark, H. (1996). Using language. New York: Cambridge University Press.CrossRefGoogle Scholar
Clark, H. H., & Schaefer, E. F. (1987). Collaborating on contributions to conversations. Language & Cognitive Processes, 2, 1941.CrossRefGoogle Scholar
Coltheart, M. (1981). The MRC psycholinguistics database. Quarterly Journal of Experimental Psychology, 33A, 497505.CrossRefGoogle Scholar
Colwell, K., Hiscock, C. K., & Memon, A. (2002). Interviewing techniques and the assessment of statement credibility. Applied Cognitive Psychology, 16, 287300.CrossRefGoogle Scholar
Crossley, S., Louwerse, M., McCarthy, P. M., & McNamara, D. S. (2007). A linguistic analysis of simplified and authentic texts. Modern Language Journal, 91, 1530.CrossRefGoogle Scholar
DePaulo, B. M., Lindsay, J. J., Malone, B. E., Muhlenbruck, L., Charlton, K., & Cooper, H. (2003). Cues to deception. Psychological Bulletin, 129, 74118.CrossRefGoogle ScholarPubMed
Duran, N. D., Bellissens, C., Taylor, R., & McNamara, D. S. (2007). Quantifying text difficulty with automated indices of cohesion and semantics. In McNamara, D. S. & Trafton, G. (Eds.), Proceedings of the 29th Annual Meeting of the Cognitive Science Society (pp. 233238). Austin, TX: Cognitive Science Society.Google Scholar
Garrod, S., & Anderson, A. (1987). Saying what you mean in dialogue: A study in conceptual and semantic co-ordination. Cognition, 27, 181218.CrossRefGoogle ScholarPubMed
Greene, J. O., O'Hair, H. D., Cody, M. J., & Yen, C. (1985). Planning and control of behavior during deception. Human Communication Research, 11, 335364.CrossRefGoogle Scholar
Graesser, A. C., McNamara, D. S., & Louwerse, M. M. (2003). What do readers need to learn in order to process coherence relations in narrative and expository text? In Sweet, A. P. & Snow, C. E. (Eds.), Rethinking reading comprehension (pp. 8298). New York: Guilford Press.Google Scholar
Graesser, A. C., McNamara, D. S., Louwerse, M. M., & Cai, Z. (2004). Coh-Metrix: Analysis of text on cohesion and language. Behavior Research Methods, Instruments, and Computers, 36, 193202.CrossRefGoogle ScholarPubMed
Graesser, A. C., Zhiqiang, C., Louwerse, M. M., & Daniel, F. (2006). Question Understanding Aid (QUAID): A web facility that helps survey methodologists improve the comprehensibility of questions. Public Opinion Quarterly, 70, 322.CrossRefGoogle Scholar
Grice, P. H. (1975). Logic and conversation. In Cole, P. & Morgan, J. (Eds.), Syntax and semantics (Vol. 3, pp. 4158). New York: Academic Press.Google Scholar
Hancock, J. T., Curry, L., Goorha, S., & Woodworth, M. T. (2008). On lying and being lied to: A linguistic analysis of deception. Discourse Processes, 45, 123.CrossRefGoogle Scholar
Hempelmann, C., Rus, V., Graesser, A., & McNamara, D. (2006). Evaluating state-of-the-art treebank-style parsers for Coh-Metrix and other learning technology environments. Natural Language Engineering, 12, 131144.CrossRefGoogle Scholar
Hempelmann, C. F., Dufty, D., McCarthy, P. M., Graesser, A. C., Cai, Z, & McNamara, D. S. (2005). Using LSA to automatically identify givenness and newness of noun phrases in written discourse. In Bara, B. G., Barsalou, L., & Bucciarelli, M. (Eds.), Proceedings of the 27th Annual Conference of the Cognitive Science Society (pp. 941946). Mahwah, NJ: Erlbaum.Google Scholar
Johnson, M. K., & Raye, C. L. (1981). Reality monitoring. Psychological Review, 88, 6785.CrossRefGoogle Scholar
Johnson, R., Barnhardt, J., & Zhu, J. (2004). The contribution of executive processes to deceptive responding. Neuropsychologia, 42, 878901.CrossRefGoogle ScholarPubMed
Juul Andersen, T. (2005). The performance effect of computer-mediated communication and decentralized strategic decision making. Journal of Business Research, 58, 10591067.CrossRefGoogle Scholar
Kahn, J., Tobin, R., Massey, A., & Anderson, J. (2007). Measuring emotional expression with the Linguistic Inquiry and Word Count. American Journal of Psychology, 120, 263286.CrossRefGoogle ScholarPubMed
Landauer, T., McNamara, D. S., Dennis, S., & Kintsch, W. (Eds.). (2007). LSA: A road to meaning. Mahwah, NJ: Erlbaum.Google Scholar
McCarthy, P. M., Dufty, D., Hempelman, C., Cai, Z., Graesser, A. C., & McNamara, D. S. (in press). Evaluating givenness/newness. Discourse Processes.Google Scholar
McCarthy, P. M., Lewis, G. A., Dufty, D. F., & McNamara, D. S. (2006). Analyzing writing styles with Coh-Metrix. In Sutcliffe, G. C. J. & Goebel, R. G. (Eds.), Proceedings of the 19th International Florida Artificial Intelligence Research Society Conference (pp. 764770). Menlo Park, CA: AAAI Press.Google Scholar
McCarthy, P. M., Renner, A. M., Duncan, M. G., Duran, N. D., Lightman, E. J., & McNamara, D. S. (2008). Identifying topic sentencehood. Behavior Research Methods, 40, 647664.CrossRefGoogle ScholarPubMed
McNamara, D. S., Kintsch, E., Songer, B. N., & Kintsch, W. (1996). Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from texts. Cognition and Instruction, 14, 143.CrossRefGoogle Scholar
McNamara, D. S., Louwerse, M. M., McCarthy, P. M., & Graesser, A. C. (in press). Coh-Metrix: Capturing linguistic features of cohesion. Discourse Processes.Google Scholar
McNamara, D. S., Ozuru, Y., Graesser, A. C., & Louwerse, M. (2006). Validating Coh-Metrix. In Sun, R. & Miyake, N. (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 573578). Austin, TX: Cognitive Science Society.Google Scholar
Miller, G. (1990). Introduction to WordNet: An on-line lexical database. International Journal of Lexicography, 3, 235312.CrossRefGoogle Scholar
Newman, M. L., Pennebaker, J. W., Berry, D. S., & Richards, J. M. (2003). Lying words: Predicting deception from linguistic styles. Personality and Social Psychology Bulletin, 29, 665675.CrossRefGoogle ScholarPubMed
Niederhoffer, K. G., & Pennebaker, J. W. (2002). Linguistic style matching in social interaction. Journal of Language and Social Psychology, 21, 337.CrossRefGoogle Scholar
Ozuru, Y., Best, R., & McNamara, D. S. (2004). Contribution of reading skill to learning from expository texts. In Forbus, K., Gentner, D., & Regier, T. (Eds.), Proceedings of the 26th Annual Cognitive Science Society (pp. 10711076). Mahwah, NJ: Erlbaum.Google Scholar
Paivio, A. (1969). Mental Imagery in associative learning and memory. Psychological Review, 76, 241263.CrossRefGoogle Scholar
Pennebaker, J. W., Francis, M. E., & Booth, R. J. (2001). Linguistic Inquiry and Word Count: LIWC 2001. Mahwah, NJ: Erlbaum.Google Scholar
Pennebaker, J. W., & King, L. A. (1999). Linguistic styles: Language use as an individual difference. Journal of Personality and Social Psychology, 77, 12961312.CrossRefGoogle ScholarPubMed
Pennebaker, J. W., Mayne, T. J., & Francis, M. E. (1997). Linguistic predictors of adaptive bereavement. Journal of Personality and Social Psychology, 72, 863871.CrossRefGoogle ScholarPubMed
Pennebaker, J. W., Mehl, M. R., & Niederhoffer, K. G. (2003). Psychological aspects of natural language use: Our words, our selves. Annual Reviews in Psychology, 54, 547577.CrossRefGoogle ScholarPubMed
Pickering, M., & Garrod, S. (2004). Toward a mechanistic psychology of dialogue. Behavioral and Brain Sciences, 27, 169226.CrossRefGoogle Scholar
Quan-Haase, A., Cothrel, J., & Wellman, B. (2005). Instant messaging for collaboration: A case study of a high-tech firm. Journal of Computer-Mediated Communication, 10, article 13. Retrieved from http://jcmc.indiana.edu/vol10/issue4/quan-haase.htmlCrossRefGoogle Scholar
Stevens, J. P. (2002). Applied multivariate statistics for the social sciences. Mahwah, NJ: Erlbaum.Google Scholar
Underwood, B. J., & Schulz, R. W. (1960). Meaningfulness and verbal learning. Philadelphia, PA: Lippincott.Google Scholar
Vrij, A., Edward, K., Roberts, K., & Bull, R. (2000). Detecting deceit via analysis of verbal and nonverbal behavior. Journal of Nonverbal Behavior, 24, 239263.CrossRefGoogle Scholar
Vrij, A., & Heaven, S. (1999). Vocal and verbal indicators of deception as a function of lie complexity. Psychology, Crime & Law, 5, 203215.Google Scholar
Wiener, M., & Mehrabian, A. (1968). Language within language: Immediacy, a channel in verbal communication. New York: Appleton–Century–Crofts.Google Scholar
Zhou, L. (2005). An empirical investigation of deception behavior in instant messaging. IEEE Transactions on Professional Communication, 48, 147160.CrossRefGoogle Scholar
Zhou, L., Burgoon, J. K., Nunamaker, J. F., & Twitchell, D. (2004). Automating linguistics-based cues for detecting deception in text-based asynchronous computer-mediated communications. Group Decision and Negotiation, 13, 81106.CrossRefGoogle Scholar
Zuckerman, M., DePaulo, B. M., & Rosenthal, R. (1981). Verbal and nonverbal communication of deception. In Berkowitz, L. (Ed.), Advances in experimental social psychology (Vol. 14, pp. 159). New York: Academic Press.Google Scholar