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

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Advances in Fuzzy Logic and Technology 2017 (EUSFLAT 2017, IWIFSGN 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 641))

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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.

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Acknowledgments

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

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Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain

    Juan Bernabé-Moreno, Alvaro Tejeda-Lorente & Enrique Herrera-Viedma

  2. Department of Computer Science, University of Jaén, Jaén, Spain

    Carlos Porcel

Authors
  1. Juan Bernabé-Moreno
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  2. Alvaro Tejeda-Lorente
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  3. Carlos Porcel
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  4. Enrique Herrera-Viedma
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Corresponding author

Correspondence to Enrique Herrera-Viedma .

Editor information

Editors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Eulalia Szmidt

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Sławomir Zadrożny

  4. Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Krassimir T. Atanassov

  5. WIT - Warsaw School of Information Technology, Warsaw, Poland

    Maciej Krawczak

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Bernabé-Moreno, J., Tejeda-Lorente, A., Porcel, C., Herrera-Viedma, E. (2018). A Fuzzy Linguistics Supported Model to Measure the Contextual Bias in Sentiment Polarity. In: Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K., Krawczak, M. (eds) Advances in Fuzzy Logic and Technology 2017. EUSFLAT IWIFSGN 2017 2017. Advances in Intelligent Systems and Computing, vol 641. Springer, Cham. https://doi.org/10.1007/978-3-319-66830-7_19

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  • DOI: https://doi.org/10.1007/978-3-319-66830-7_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66829-1

  • Online ISBN: 978-3-319-66830-7

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