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Detecting Deception through Linguistic Analysis

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2665)

Abstract

Tools to detect deceit from language use pose a promising avenue for increasing the ability to distinguish truthful transmissions, transcripts, intercepted messages, informant reports and the like from deceptive ones. This investigation presents preliminary tests of 16 linguistic features that can be automated to return assessments of the likely truthful or deceptiveness of a piece of text. Results from a mock theft experiment demonstrate that deceivers do utilize language differently than truth tellers and that combinations of cues can improve the ability to predict which texts may contain deception.

Keywords

Linguistic Analysis Truth Teller Deception Detection Text Chat Deception Condition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Burgoon, J. K., Buller, D. B., Ebesu, A., Rockwell, P.: Interpersonal Deception: V: Accuracy in Deception Detection. Communication Monographs 61 (1994) 303–325CrossRefGoogle Scholar
  2. 2.
    Levine, T., McCornack, S.: Linking Love and Lies: A Formal Test of the McCornack and Parks Model of Deception Detection. J. of Social and Personal Relationships 9 (1992) 143–154CrossRefGoogle Scholar
  3. 3.
    Zuckerman, M., DePaulo, B., Rosenthal, R.: Verbal and Nonverbal Communication of Deception. In: Berkowitz, L. (ed.): Advances in Experimental Social Psychology, Vol. 14. Academic Press, New York (1981) 1–59Google Scholar
  4. 4.
    Burgoon, J., Blair, J. P., Moyer, E.: Effects of Communication Modality on Arousal, Cognitive Complexity, Behavioral Control and Deception Detection during Deceptive Episodes. Paper submitted to the Annual Meeting of the National Communication Association, Miami. (2003, November)Google Scholar
  5. 5.
    Burgoon, J., Marett, K., Blair, J. P.: Detecting Deception in Computer-Mediated Communication. In: George, J. F. (ed.): Computers in Society: Privacy, Ethics & the Internet. Prentice-Hall, Upper Saddle River, NJ (in press)Google Scholar
  6. 6.
    Vrij, A.: Detecting Lies and Deceit. John Wiley and Sons, New York (2000)Google Scholar
  7. 7.
    Inbau, F. E., Reid, J. E., Buckley, J. P., Jayne, B. C.: Criminal Interrogations and Confessions. 4th edn. Aspen, Gaithersburg, MD (2001)Google Scholar
  8. 8.
    Quinlan, J. R.: C4.5. Morgan Kaufmann Publishers, San Mateo, CA (1993)Google Scholar
  9. 9.
    Spangler, W., May, J., Vargas, L.: Choosing Data-Mining Methods for Multiple Classification: Representational and Performance Measurement Implications for Decision Support. J. Management Information Systems 16 (1999) 37–62Google Scholar
  10. 10.
    Zhou, L. Twitchell, D., Qin, T., Burgoon, J. K., Nunamaker, J. F., Jr.: An Exploratory Study into Deception Detection in Text-based Computer-Mediated Communication. In: Proceedings of the 36th Annual Hawaii International Conference of System Sciences. Big Island, Los Alamitos, CA (2003)Google Scholar
  11. 11.
    Buller, D. B., Burgoon, J. K.: Interpersonal Deception Theory. Communication Theory 6 (1996) 203–242CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  1. 1.Center for the Management of InformationUniversity of ArizonaUSA
  2. 2.Department of Criminal JusticeMichigan State UniversityUSA

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