Seeing through Deception: A Computational Approach to Deceit Detection in Spanish Written Communication

Authors

  • Ángela Almela Universidad Católica San Antonio de Murcia
  • Rafael Valencia-García Universidad de Murcia
  • Pascual Cantos Universidad de Murcia

DOI:

https://doi.org/10.5195/lesli.2013.5

Keywords:

deception detection, opinion mining, Support Vector Machine, bag of words

Abstract

The present paper addresses the question of the nature of deception language. Specifically, the main aim of this piece of research is the exploration of deceit in Spanish written communication. We have designed an automatic classifier based on Support Vector Machines (SVM) for the identification of deception in an ad hoc opinion corpus. In order to test the effectiveness of the LIWC2001 categories in Spanish, we have drawn a comparison with a Bag-of-Words (BoW) model. The results indicate that the classification of the texts is more successful by means of our initial set of variables than with the latter system. These findings are potentially applicable to areas such as forensic linguistics and opinion mining, where extensive research on languages other than English is needed.

Author Biographies

Ángela Almela, Universidad Católica San Antonio de Murcia

Associate Professor, Modern Languages Department, Universidad Católica San Antonio de Murcia

Rafael Valencia-García, Universidad de Murcia

Professor, Computer Sciences and Systems, Universidad de Murcia

Pascual Cantos, Universidad de Murcia

Professor, English Department, Universidad de Murcia

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Published

2013-12-06

Issue

Vol. 1 No. 1 (2013)

Section

Research Articles

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