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Sentiment Analysis on TripAdvisor: Are There Inconsistencies in User Reviews?

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Hybrid Artificial Intelligent Systems (HAIS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10334))

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Abstract

The number of online reviews has grown exponentially over the last years. As a result, several Sentiment Analysis Methods (SAMs) have been developed in order to extract automatically sentiments from text. In this work, we study polarity coherencies between reviewers and SAMs. To do so, we compare the polarity of the document evaluated by the user and the aggregated sentence polarity evaluated by three SAMs. The main contribution of this work is to show the flimsiness of user ratings as a generalization of the overall review sentiment.

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Notes

  1. 1.

    https://www.tripadvisor.com.

  2. 2.

    https://en.wikipedia.org/wiki/TripAdvisor.

  3. 3.

    Source: TripAdvisor log files, Q1 2016.

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We thank the anonymous reviewers for their constructive feedback. This research has been supported by FEDER and the Spanish National Research Project TIN2014-57251-P.

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Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, 18071, Granada, Spain

    Ana Valdivia & Francisco Herrera

  2. Department of Software Engineering, University of Granada, 18071, Granada, Spain

    M. Victoria Luzón

Authors
  1. Ana Valdivia
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  2. M. Victoria Luzón
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  3. Francisco Herrera
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Corresponding author

Correspondence to Ana Valdivia .

Editor information

Editors and Affiliations

  1. University of La Rioja , Logroño, La Rioja, Spain

    Francisco Javier Martínez de Pisón

  2. University of La Rioja , Logroño, La Rioja, Spain

    Rubén Urraca

  3. University of A Coruña , Ferrol, La Coruña, Spain

    Héctor Quintián

  4. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Valdivia, A., Luzón, M.V., Herrera, F. (2017). Sentiment Analysis on TripAdvisor: Are There Inconsistencies in User Reviews?. In: Martínez de Pisón, F., Urraca, R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2017. Lecture Notes in Computer Science(), vol 10334. Springer, Cham. https://doi.org/10.1007/978-3-319-59650-1_2

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  • DOI: https://doi.org/10.1007/978-3-319-59650-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59649-5

  • Online ISBN: 978-3-319-59650-1

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