Authorship Attribution of Brazilian Literary Texts Through Machine Learning Techniques

Abstract

Authorship attribution is the process of identifying the author of a particular document. This task has been performed by experts in the field. However, with the advancement of natural language processing tools and machine learning techniques, this activity has also been performed by computer systems. Authorship attribution has applicability from the detection of plagiarism and copyright to the resolution of forensic problems. There are several works on this subject in the English idiom, however those that consider texts in Portuguese are few. Therefore, this paper aims to study authorship attribution of texts of Brazilian literature. We carried out our experiments using Naïve Bayes and Random Forests methods, and for the feature extraction we considered Term Frequency - Inverse Document Frequency and Part of Speech techniques. The results showed that the Random Forests using as input the textual features extracted by Part of Speech presented the best cross-validation accuracy, although not the best runtime.