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Negative Sentiments Make Review Sentences Longer: Evidence from Japanese Hotel Review Sites

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14376))

Abstract

Existing research on the psychology of the posters of customer reviews has mainly focused on their motivation for posting. However, there is little discussion about understanding the feelings of contributors based on review characteristics. This study used big data from a hotel reservation website Rakuten Travel, provided by Rakuten Group, Inc., a major Japanese IT company, and investigated the relationship between the number of characters in reviews and ratings. A multiple regression analysis showed that, the more words in the review, the lower the overall rating. Furthermore, the lower the rating of the individual items (location, room, meal, bath, service), the greater the negative effect of the number of characters in the review on the overall rating. Similarly, when only negative expressions were detected, the negative effect of review word count on overall rating was greater. Practitioners should recognize that customers are more likely to communicate negative than positive emotions. Consumers are less likely to express their emotional attitudes through writing than speaking. This is because, in the process of writing, there is more time to ponder on things to say and less emotion. Therefore, a strong negative feeling is associated with posting a long sentence with considerable effort. Practitioners should include both rating figures and review characteristics as variables in customer churn prediction models. It is effective for customer understanding to identify the generation mechanism for review features that cannot be comprehended at a glance.

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Acknowledgement

This study used “Rakuten Dataset” (https://rit.rakuten.com/data_release/) provided by Rakuten Group, Inc. Via IDR Dataset Service of National Institute of Informatics.

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Authors and Affiliations

  1. School of Commerce, Meiji University, Tokyo, Japan

    Takumi Kato

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  1. Takumi Kato
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Correspondence to Takumi Kato .

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Editors and Affiliations

  1. Osaka Metropolitan University, Sakai, Osaka, Japan

    Katsuhiro Honda

  2. Vietnam National University, Ho Chi Minh City, Vietnam

    Bac Le

  3. Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Van-Nam Huynh

  4. Osaka University, Toyonaka, Osaka, Japan

    Masahiro Inuiguchi

  5. Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Youji Kohda

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Kato, T. (2023). Negative Sentiments Make Review Sentences Longer: Evidence from Japanese Hotel Review Sites. In: Honda, K., Le, B., Huynh, VN., Inuiguchi, M., Kohda, Y. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2023. Lecture Notes in Computer Science(), vol 14376. Springer, Cham. https://doi.org/10.1007/978-3-031-46781-3_24

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  • DOI: https://doi.org/10.1007/978-3-031-46781-3_24

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  • Online ISBN: 978-3-031-46781-3

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