Detectando la mentira en lenguaje escrito

  1. Almela Sánchez-Lafuente, Ángela
  2. Valencia García, Rafael
  3. Cantos Gómez, Pascual
Revista:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Año de publicación: 2012

Número: 48

Páginas: 65-72

Tipo: Artículo

DIALNET GOOGLE SCHOLAR lock_openRUA editor

Otras publicaciones en: Procesamiento del lenguaje natural

Resumen

Deception in language has been studied from the perspective of several disciplines, being the most recent one opinion mining. Within this framework, the present study attempts to explore deception cues in written Spanish, which, to the best of our knowledge, has not been investigated yet. For our purposes, we have developed a framework based on a classifier using a Support Vector Machine (SVM) in order to detect deception in an ad hoc opinion corpus. We have used the psycholinguistic categories defined in LIWC (Pennebaker, Francis and Booth, 2001) through its four broad dimensions for the subsequent training of the abovementioned classifier. The findings reveal that truthful and deceptive texts in Spanish are indeed separable, being the two first dimensions, linguistic and psychological processes, the most relevant ones for fulfilling our aim.

Referencias bibliográficas

  • Alpers, G. W., A. Winzelberg, C. Classen, H. Roberts, P. Dev, C. Koopman, y B. Taylor. 2005. Evaluation of computerized text analysis in an Internet breast cancer support group. Computers in Human Behavior, 21:361-376.
  • Bishop, J. 2009. Enhancing the understanding of genres of web-based communities: The role of the ecological cognition framework. International Journal of Web-Based Communities, 5(1):4-17.
  • Bond, G. D. y A. Y. Lee. 2005. Language of lies in prison: Linguistic classification of prisoners’ truthful and deceptive natural language. Applied Cognitive Psychology, 19:313-329.
  • Bouckaert, R. R., E. Frank, M. A. Hall, G. Holmes, B. Pfahringer, P. Reutemann, y I. H. Witten. 2010. WEKA-experiences with a java open-source project. Journal of Machine Learning Research, 11:2533-2541.
  • Burgoon, J. K., J. P. Blair, T. Qin, y J. F. Nunamaker. 2003. Detecting deception through linguistic analysis. Intelligence and Security Informatics, 2665:91-101.
  • Chung, C. y J. W. Pennebaker. 2007. The psychological functions of function words. En K. Fiedler (Ed.), Social Communication, páginas 343-359, Psychology Press (New York).
  • Coulthard. M. 2004. Author identification, idiolect, and linguistic uniqueness. Applied Linguistics, 25(4):431-447.
  • DePaulo, B. M., D. A. Kashy, S. E. Kirkendol, M. M. Wyer, y J. A. Epstein. 1996. Lying in everyday life. Journal of Personality and Social Psychology, 70:979-995.
  • Fornaciari, T. y M. Poesio. 2011. Lexical vs. Surface Features in Deceptive Language Analysis. En Proceedings of the ICAIL 2011 Workshop Applying Human Language Technology to the Law, páginas 2-8, Pittsburgh (Alemania).
  • Granhag, P. A. y L. A. Strömwall. 2004. The Detection of Deception in Forensic Contexts. Cambridge University Press, Cambridge.
  • Hancock, J. T., L. E. Curry, S. Goorha, y M. T. Woodworth. 2004. Lies in conversation: an examination of deception using automated linguistic analysis. En Proceedings of the Annual Conference of the Cognitive Science Society, páginas 1-6, Taylor and Francis Group, Psychology Press, Mahwah (EE.UU.).
  • Hancock, J. T., L. E. Curry, S. Goorha, y M. T. Woodworth. 2008. On lying and being lied to: A linguistic analysis of deception in computer-mediated communication. Discourse Processes, 45:1-23.
  • Labov, W. 1972. Sociolinguistic Patterns. Oxford: Blackwell.
  • Leshed, G., J. T. Hancock, D. Cosley, P. L. McLeod, y G. Gay. 2007. Feedback for guiding reflection on teamwork practices. En Proceedings of the GROUP’07 Conference on Supporting Group Work, páginas 217-220, Association for Computing Machinery Press, New York (EE.UU.).
  • Lewis, D. 1998. Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval. En Proceedings of ECML-98, 10th European Conference on Machine Learning, páginas 4-15, Springer Verlag, Heidelberg (Alemania).
  • Mairesse, F., M. A. Walker, M. Mehl, y R. K. Moore. 2007. Using linguistic cues for the automatic recognition of personality in conversation and text. Journal of Artificial Intelligence Research, 30(1):457-500.
  • Mihalcea, R. y C. Strapparava. 2009. The Lie Detector: Explorations in the Automatic Recognition of Deceptive Language. En Proceedings of the Association for Computational Linguistics, ACL-IJCNLP, páginas 309-312, Singapur (Singapur).
  • Newman, M. L., J. W. Pennebaker, D. S. Berry, y J. M. Richards. 2003. Lying words: Predicting deception from linguistic styles. Personality and Social Psychology Bulletin, 29:665-675.
  • Ott, M., Y. Choi, C. Cardie, y J. T. Hancock. 2011. Finding deceptive opinion spam by any stretch of the imagination. En Proceedings of ACL, páginas 309-319, Portland (EE.UU.).
  • Pennebaker, J. W., M. E. Francis, y R. J. Booth. 2001. Linguistic Inquiry and Word Count. Erlbaum Publishers, Mahwah (NJ).
  • Pennebaker, J. W., C. K. Chung, M. Ireland, A. L. Gonzales, y R. J. Booth. 2007. The Development and Psychometric Properties of LIWC2007. LIWC.net, Austin (TX).
  • Picornell, I. 2011. The Rake’s Progress: Mapping deception in written witness statements. Comunicación oral presentada en el International Association of Forensic Linguists Tenth Biennial Conference, Birmingham (RU).
  • Ramírez-Esparza, N., J. W. Pennebaker, y F. A. García. 2007. La psicología del uso de las palabras: Un programa de computadora que analiza textos en español. Revista Mexicana de Psicología, 24:85-99.
  • Rude, S. S., E. M. Gortner, y J. W. Pennebaker. 2004. Language use of depressed and depression-vulnerable college students. Cognition and Emotion, 18:1121-1133.
  • Rushdi-Saleh, M., M. T. Martín-Valdivia, A. Montejo-Ráez, y L. A. Ureña-López. 2011. Experiments with SVM to classify opinions in different domains. Expert System with Applications, 38(12):14799-14804.
  • Tausczik, Y. R. y J. W. Pennebaker. 2010. The psychological meaning of words: LIWC and computerized text analysis methods. Journal of Language and Social Psychology, 29:24-54.
  • Vrij, A. 2010. Detecting Lies and Deceit: Pitfalls and Opportunities. 2nd edition. John Wiley and Sons, Chischester.
  • Vrij, A., S. Mann, S. Kristen, y R. P. Fisher. 2007. Cues to deception and ability to detect lies as a function of police interview styles. Law and Human Behavior, 31(5):499-518.
Fuente de los datos: Dialnet