A Corpus-Based Study of Linguistic Deception in Spanish

Abstract

In the last decade, fields such as psychology and natural language processing have devoted considerable attention to the automatization of the process of deception detection, developing and employing a wide array of automated and computer-assisted methods for this purpose. Similarly, another emerging research area is focusing on computer-assisted deception detection using linguistics, with promising results. Accordingly, in the present article, the reader is firstly provided with an overall review of the state of the art of corpus-based research exploring linguistic cues to deception as well as an overview on several approaches to the study of deception and on previous research into its linguistic detection. In an effort to promote corpus-based research in this context, this study explores linguistic cues to deception in the Spanish written language with the aid of an automatic text classification tool, by means of an ad hoc corpus containing ground truth data. Interestingly, the key findings reveal that, although there is a set of linguistic cues which contributes to the global statistical classification model, there are some discursive differences across the subcorpora, yielding better classification results on the analysis conducted on the subcorpus containing emotionally loaded language.