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A Review on Bayesian Networks for Sentiment Analysis

  • Luis Gutiérrez
  • Juan Bekios-Calfa
  • Brian Keith
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 865)

Abstract

This article presents a review of the literature on the application of Bayesian networks in the field of sentiment analysis. This is done in the context of a research project on text representation and use of Bayesian networks for the determination of emotions in the text. We have analyzed relevant articles that correspond mainly to two types, some in which Bayesian networks are used directly as classification methods and others in which they are used as a support tool for classification, by extracting features and relationships between variables. Finally, this review presents the bases for later works that seek to develop techniques for representing texts that use Bayesian networks or that, through an assembly scheme, allow for superior classification performance.

Keywords

Bayesian networks Sentiment analysis Literature review Opinion mining 

Notes

Acknowledgments

Research partially funded by the National Commission of Scientific and Technological Research (CONICYT) and the Ministry of Education of the Government of Chile. Project REDI170607: “Multidimensional Bayesian classifiers for the interpretation of text and video emotions”.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Luis Gutiérrez
    • 1
  • Juan Bekios-Calfa
    • 1
  • Brian Keith
    • 1
  1. 1.Department of Computing and Systems EngineeringUniversidad Católica del NorteAntofagastaChile

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