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An Examination and Validation of Linguistic Constructs for Studying High-Stakes Deception

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Abstract

Theories of deception have produced upwards of 150 potential verbal and nonverbal communication indicators. Of these, approximately 30 indicators, or cues, have been used previously with automated linguistic analysis tools to study text-based communication. The current research examines the interrelationships among these cues and proposes a set of specific constructs to be validated for high-stakes deception research. We analyzed linguistic-based cues extracted from 367 written statements prepared by suspects and victims of crimes on military bases. Confirmatory factor analysis was used to evaluate two models. The superior model retained seven constructs: quantity, specificity, affect, diversity, uncertainty, nonimmediacy, and activation.

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References

  • American heritage dictionary (1991) 2nd College edn. Houghton Mifflin, Boston

  • Bagozzi R (2010) Structural equation models are modeling tools with many ambiguities: comments acknowledging the need for caution and humility in their use. J Consumer Psychol 20: 208–214

    Article  Google Scholar 

  • Bond CF, DePaulo BM (2006) Accuracy of deception judgments. Pers Soc Psychol Rep 10: 214–234

    Article  Google Scholar 

  • Bond GD, Lee AY (2005) Language of lies in prison: linguistic classification of prisoners’ truthful and deceptive natural language. Appl Cogn Psychol 19: 313–329

    Article  Google Scholar 

  • Buller DB, Burgoon JK (1996) Interpersonal deception theory. Commun Theory 6: 203–242

    Article  Google Scholar 

  • Burgoon JK, Qin TT (2006) The dynamic nature of deceptive verbal communication. J Lang Soc Psychol 25: 1–22

    Article  Google Scholar 

  • Burgoon JK, Burgoon M, Wilkinson M (1981) Writing style as a predictor of newspaper readership, satisfaction and image. Journal Q 58: 225–231

    Article  Google Scholar 

  • Burgoon JK, Buller DB, Guerroro LK, Afifi W, Feldman C (1996) Interpersonal deception: Xii. Information management dimensions underlying deceptive and truthful messages. Commun Monogr 63: 50–69

    Article  Google Scholar 

  • Burgoon JK, Blair JP, Qin TT, Nunamaker JF (2003) Detecting deception through linguistic analysis. In: Lecture notes in computer science: intelligence and security informatics 2665. Springer, Berlin, pp 91–101

  • Cao J, Crews JM, Lin M, Burgoon J, Nunamaker JF (2003) Designing agent99 trainer: a learner-centered, web-based training system for deception detection. In: Lecture notes in computer science: intelligence and security informatics 2665. Springer, Berlin, pp 358–365

  • Chin WW, Todd PA (1995) On the use, usefullness, and ease of use of structural equation modeling in mis research: a note of caution. MIS Q 19: 237–246

    Article  Google Scholar 

  • Cunningham H (2002) Gate, a general architecture for text engineering. Comput Humanit 36: 223–254

    Article  Google Scholar 

  • Cunningham H, Maynard D, Bontcheva K, Tablan V, Ursu C, Dimitrov M, Dowman M, Aswani N, Roberts I (2005) Developing language processing components with gate version 3 (a user guide) http://gate.Ac.Uk/sale/tao/index.Html#x1-1710008.4

  • DePaulo BM, Lindsay JJ, Malone BE, Muhlenbruck L, Charlton K, Cooper H (2003) Cues to deception. Psychol Bull 129: 74–118

    Article  Google Scholar 

  • Ekman P (1985) Telling lies: clues to deceit in the marketplace, politics, and marriage. WW Norton & Company, New York

    Google Scholar 

  • Ford EB (2006) Lie detection: historical, neuropsychiatric and legal dimensions. Int J Psychiatry 29: 159–177

    Article  Google Scholar 

  • Frank MG, Feeley TH (2003) To catch a liar: challenges for research in lie detection training. J Appl Commun Res 31: 58–75

    Article  Google Scholar 

  • Fuller C, Biros D, Wilson R (2009) Decision support for determining veracity via linguistic-based cues. Decis Support Syst 46: 695–703

    Article  Google Scholar 

  • Fuller C, Biros DP, Adkins M, Burgoon J, Nunamaker JF Jr, Coulon S (2006a) Detecting deception in person-of-interest statements. In: Lecture notes in computer science 3975. Springer, Berlin, pp 504–509

  • Fuller C, Biros DP, Twitchell D, Burgoon J, Adkins M (2006b) An analysis of text-based deception detection tools. In: Proceedings of twelfth Americas conference on information systems. Acapulco, Mexico, August 4–6

  • Hair JF, Anderson RE, Tatham RL, Black WC (1998) Multivariate data analysis, 5th edn. Prentice-Hall, Upper Saddle River

    Google Scholar 

  • Hu L, Bentler PM (1998) Fit indexes in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychol Methods 3: 424–453

    Article  Google Scholar 

  • Hu L, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model 6: 1–55

    Article  Google Scholar 

  • Iacobucci D (2010) Structural equations modeling: fit indices, sample size, and advanced topics. J Consum Psychol 20: 90–98

    Article  Google Scholar 

  • Johnson MK, Raye CL (1981) Reality monitoring. Psychol Rev 88: 67–85

    Article  Google Scholar 

  • Kelloway EK (1998) Using lisrel for structural equation modeling: a researcher’s guide. SAGE Publications, Thousand Oaks

    Google Scholar 

  • Knapp ML, Hart RP, Dennis HS (1974) An exploration of deception as a communication construct. Human Commun Res 1: 15–29

    Article  Google Scholar 

  • McCornack SA (1992) Information manipulation theory. Commun Monogr 59: 1–16

    Article  Google Scholar 

  • Newman ML, Pennebaker JW, Berry DS, Richards JM (2003) Lying words: predicting deception from linguistic styles. Pers Soc Psychol Bull 29: 665–675

    Article  Google Scholar 

  • Pedhazur EJ, Schmelkin LP (1991) Measurement, design, and analysis: an integrated approach. Lawrence Erlbaum Associates, Hillsdale

    Google Scholar 

  • Pennebaker JW, Francis ME (2001) Linguistic inquiry and word count: LIWC 2001. Erlbaum Publishers, Mahwah NJ

    Google Scholar 

  • Porter S, Yuille JC (1996) The language of deceit: an investigation of the verbal clues to deception in the interrogation context. Law Hum Behav 20: 443–458

    Article  Google Scholar 

  • Pyle D (1999) Data preparation for data mining. Morgan Kaufmann Publishers, San Francisco

    Google Scholar 

  • Qin T, Burgoon J, Nunamaker JF (2004) An exploratory study on promising cues in deception detection and application of decision tree. In: Proceedings of 37th annual hawaii international conference on system sciences

  • Sporer SL (2004) Reality monitoring and detection of deception. In: Granhag P (ed) He detection of deception in forensic contexts. Cambridge University Press, Cambridge, pp 64–102

    Chapter  Google Scholar 

  • Twitchell DP, Biros DP, Adkins M, Forsgren N, Burgoon JK, Nunamaker JF Jr (2006) Automated determination of the veracity of interview statements from people of interest to an operational security force. In: Proceedings of 39th annual Hawaii international conference on system sciences

  • Vrij A (2000) Detecting lies and deceit: the psychology of lying and the implications for professional practice. Wiley, New York

    Google Scholar 

  • Vrij A, Mann S (2001) Who killed my relative? Police officers’ ability to detect real-life high-stake lies. Psychol Crime Law 7: 119–132

    Article  Google Scholar 

  • Vrij A, Edward K, Roberts KP, Bull R (2000) Detecting deceit via analysis of verbal and nonverbal behavior. J Nonverbal Behav 24: 239–263

    Article  Google Scholar 

  • Whissell C (1989) The dictionary of affect in language. In: Plutchik R, Kellerman H (eds) Emotion theory, research and experience: the measurement of emotions, vol. 4. Academic Press, London, pp 113–131

    Google Scholar 

  • Witten IH, Frank E (2000) Data mining: practical machine learning tools and techniques with java. Morgan Kaufman, San Francisco

    Google Scholar 

  • Zhou L, Zhang DS (2006) A comparison of deception behavior in dyad and triadic group decision making in synchronous computer-mediated communication. Small Group Res 37: 140–164

    Article  Google Scholar 

  • Zhou L, Burgoon JK, Twitchell DP (2003a) A longitudinal analysis of language behavior of deception in e-mail. In: Lecture notes in computer science: intelligence and security informatics 2665. Springer, Berlin, pp 102–110

  • Zhou L, Twitchell DP, Qin TT, Burgoon JK, Nunamaker JF Jr (2003b) An exploratory study into deception detection in text-based computer-mediated communication. In: Proceedings of 36th annual Hawaii international conference on system sciences

  • Zhou L, Burgoon JK, Nunamaker J, Jay F., Twitchell DP (2004a) Automated linguistics based cues for detecting deception in text-based asynchronous computer-mediated communication: an empirical investigation. Group Decis Negotiat 13: 81–106

    Article  Google Scholar 

  • Zhou L, Burgoon JK, Twitchell DP, Qin TT, Nunamaker JF (2004b) A comparison of classification methods for predicting deception in computer-mediated communication. J Manag Inf Syst 20: 139–165

    Google Scholar 

  • Zuckerman M, Driver RE (1985) Telling lies: verbal and nonverbal correlates of deception. In: Siegman AW, Feldstein S (eds) Multichannel integration of nonverbal behavior. Erlbaum, Hillsdale, pp 129–147

    Google Scholar 

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Correspondence to David P. Biros.

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Fuller, C.M., Biros, D.P., Burgoon, J. et al. An Examination and Validation of Linguistic Constructs for Studying High-Stakes Deception. Group Decis Negot 22, 117–134 (2013). https://doi.org/10.1007/s10726-012-9300-z

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