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

  • Ellen Souza
  • Douglas Vitório
  • Dayvid Castro
  • Adriano L. I. Oliveira
  • Cristine Gusmão
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9727)

Abstract

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. Naïve 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.

Keywords

Text mining Text classification Opinion mining Sentiment analysis Portuguese language 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ellen Souza
    • 1
    • 2
  • Douglas Vitório
    • 1
  • Dayvid Castro
    • 1
  • Adriano L. I. Oliveira
    • 2
  • Cristine Gusmão
    • 3
  1. 1.MiningBR Research GroupFederal Rural University of Pernambuco (UFRPE)Serra TalhadaBrazil
  2. 2.Centro de InformáticaFederal University of Pernambuco (CIn-UFPE)RecifeBrazil
  3. 3.Programa de Pós-graduação em Engenharia Biomédica, Centro de Tecnologia e GeociênciasFederal University of Pernambuco (CTG-UFPE)RecifeBrazil

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