Detecting deception in written language

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.