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Detecting Deception through Linguistic Analysis

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Part of the book series: Lecture Notes in Computer Science ((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.

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© 2003 Springer-Verlag Berlin Heidelberg

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Burgoon, J.K., Blair, J.P., Qin, T., Nunamaker, J.F. (2003). Detecting Deception through Linguistic Analysis. In: Chen, H., Miranda, R., Zeng, D.D., Demchak, C., Schroeder, J., Madhusudan, T. (eds) Intelligence and Security Informatics. ISI 2003. Lecture Notes in Computer Science, vol 2665. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44853-5_7

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  • DOI: https://doi.org/10.1007/3-540-44853-5_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40189-6

  • Online ISBN: 978-3-540-44853-2

  • eBook Packages: Springer Book Archive

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