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An Analysis of Travelers’ Personalities and Accommodations Ratings Using Open Datasets

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Culture and Computing (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14035))

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Abstract

E-commerce can facilitate destination and facility selection for tourism purposes. To effectively harness its full potential, it is imperative to ascertain the relationship between the characteristics of hospitality facilities and user personality to adequately propose appropriate travel plan to consumers. In this study, we analyzed this relationship using substantial number of reviews on Airbnb from an open data that includes unconstructive text data and constructive numerical data on hospitality facilities. To estimate the personalities of reviewers from the reviews, IBM personality insight was employed. We conducted graphical lasso correlation analysis to reveal the relationship among quantified variables using the aforementioned methods. Consequently, we obtained some correlative combination of facility and personality characteristics. For examples, users who have high openness score prefer New Orleans rather than Las Vegas and Miami. These findings can be further explained using the big five personality traits qualitatively.

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Author information

Authors and Affiliations

  1. Chuo University, Bunkyo Tokyo, Japan

    Naoki Takahashi & Hiroko Shoji

  2. Aoyama Gakuin University, Sagamihara Kanagawa, Japan

    Yuri Hamada

Authors
  1. Naoki Takahashi
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  2. Yuri Hamada
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  3. Hiroko Shoji
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Corresponding author

Correspondence to Naoki Takahashi .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Matthias Rauterberg

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Takahashi, N., Hamada, Y., Shoji, H. (2023). An Analysis of Travelers’ Personalities and Accommodations Ratings Using Open Datasets. In: Rauterberg, M. (eds) Culture and Computing. HCII 2023. Lecture Notes in Computer Science, vol 14035. Springer, Cham. https://doi.org/10.1007/978-3-031-34732-0_33

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  • DOI: https://doi.org/10.1007/978-3-031-34732-0_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34731-3

  • Online ISBN: 978-3-031-34732-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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