Schizophrenia is a chronic neurobiological disorder whose early detection has attracted significant attentionfrom the clinical, psychiatric and also artificial intelligence communities. This latter approach has beenmainly focused on the analysis of neuroimaging and genetic data. A less explored strategy consists in exploiting the power of Natural Language Processing (NLP) algorithms applied over narrative texts producedby schizophrenic subjects. In this article, a novel dataset collected from a proper field study is presented.Also, gramatical traits discovered in narrative documents are used to build computational representations oftexts, allowing an automatic classification of discourses generated by Schizophrenic and non-Schizophrenicsubjects. The attained results showed that the use of the proposed computational representations along withMachine Learning techniques enables a novel and precise strategy to automatically detect texts produced byschizophrenic subjects.C
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