Characterizing Opinion Mining: A Systematic Mapping Study of the Portuguese Language

摘要

The growth of social media and user-generated content (UGC) on the Internet provides a huge quantity of information that allows discovering the experiences, opinions, and feelings of users or customers. Opinion Mining (OM) is a sub-field of text mining in which the main task is to extract opinions from UGC. Given that Portuguese is one of the most common spoken languages in the world, and it is also the second most frequent on Twitter, the goal of this work is to plot the landscape of current studies that relates the application of OM for Portuguese. A systematic mapping review (SMR) method was applied to search, select and to extract data from the included studies. Manual and automated searches retrieved 6075 studies up to year 2014, from which 25 articles were included. Almost 70 % of all approaches focus on the Brazilian Portuguese variant. Naive Bayes and Support Vector Machine were the main classifiers and SentiLex-PT was the most used lexical resource. Portugal and Brazil are the main contributors in processing the Portuguese language.