A Fuzzy Linguistics Supported Model to Measure the Contextual Bias in Sentiment Polarity

  • Juan Bernabé-Moreno
  • Alvaro Tejeda-Lorente
  • Carlos Porcel
  • Enrique Herrera-Viedma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 641)

Abstract

The polarity detection problem typically relies on experimental dictionaries, where terms are assigned polarity scores lacking contextual information. As a matter of fact, the polarity is highly dependant on the domain or community it is analysed, so we can speak of a contextual bias. We propose a method supported by fuzzy linguistic modelling to quantify this contextual bias and to enable the bias-aware sentiment analysis. To show how our approach work, we measure the bias of common concepts in two different domains and discuss the results.

Keywords

Sentiment analysis Polarity Linguistic modelling Fuzzy logic Contextual bias 

Notes

Acknowledgments

This paper has been developed with the FEDER financing under Projects TIN2013-40658-P and TIN2016-75850-R.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Juan Bernabé-Moreno
    • 1
  • Alvaro Tejeda-Lorente
    • 1
  • Carlos Porcel
    • 2
  • Enrique Herrera-Viedma
    • 1
  1. 1.Department of Computer Science and Artificial IntelligenceUniversity of GranadaGranadaSpain
  2. 2.Department of Computer ScienceUniversity of JaénJaénSpain

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