A computational approach for authorship attribution of literary texts using sintatic features

This paper presents a syntactic approach for the authorship attribution to literary texts. To this end, syntactic features were used in verification and identification approaches. We used also, a classification method based on dissimilarity that has been successfully applied in cases of authorship attribution. In addition, to evaluating two models, the writer-dependent model and writer-independent, we tested approaches based on polytomy and dichotomy. We also tested the impact of the redundancy, by varying the number of references for verification and identification, for short and long texts. In order to meet these goals, we conducted experiments with four different databases, which are journalistic and literary texts in Portuguese and English languages. Through a series of experiments, we showed that the proposed approach was able to surpass the results reported in the literature, in both languages. In our experiments the proposed approach achieved results higher than 90% in both languages for verification and above 75% for the identification.