An Empirical Study of Text Features for Identifying Subjective Sentences in Portuguese

Abstract

Studies in sentiment analysis have examined how different features are effective in identifying subjective sentences. Several studies on sentiment analysis exist in the literature that have already performed some evaluation of NLP classifications. However, the vast majority of them did not handle texts in the Brazilian Portuguese language, and there is no one to consider the combination of sets of text features of NLP tasks with classifiers. Therefore, in our investigation, we combined empirical features to identify subjective sentences in Portuguese and provide a comprehensive analysis of each set of features’ relative importance using a representative set of user reviews.