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Hotel online reviews: different languages, different opinions

Author

Listed:
  • Nuno Antonio

    (Instituto Universitário de Lisboa (ISCTE-IUL)
    Instituto de Telecomunicações)

  • Ana Almeida

    (Instituto Universitário de Lisboa (ISCTE-IUL)
    CISUC
    ISTAR-IUL)

  • Luis Nunes

    (Instituto Universitário de Lisboa (ISCTE-IUL)
    Instituto de Telecomunicações
    ISTAR-IUL)

  • Fernando Batista

    (Instituto Universitário de Lisboa (ISCTE-IUL)
    INESC-ID Lisboa)

  • Ricardo Ribeiro

    (Instituto Universitário de Lisboa (ISCTE-IUL)
    INESC-ID Lisboa)

Abstract

Online reviews are one of the main influencers of hotel purchase decisions. This study performs an analysis of reviews extracted from well-known online review sources in combination with hotel sales data and concludes that ratings differ according to the language of reviews. Data science tools have been applied to English, Spanish, and Portuguese reviews, revealing that reviews written in English achieve higher ratings when compared with Spanish or Portuguese reviews. A new visualization method is proposed to quickly depict the sentiment of main topics mentioned in reviews, clearly revealing that not all customers are influenced by reviews in the same way or look for the same things in a hotel. This study has great implications for online reviews research and for hotel management as it clearly shows that language can be used to identify preferences of guests from different origins and because it gives hoteliers more information on how to provide a better service according to guests’ cultural background.

Suggested Citation

  • Nuno Antonio & Ana Almeida & Luis Nunes & Fernando Batista & Ricardo Ribeiro, 2018. "Hotel online reviews: different languages, different opinions," Information Technology & Tourism, Springer, vol. 18(1), pages 157-185, April.
    • Handle: RePEc:spr:infott:v:18:y:2018:i:1:d:10.1007_s40558-018-0107-x
    DOI: 10.1007/s40558-018-0107-x
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    References listed on IDEAS

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    1. Douglas Dow & Amal Karunaratna, 2006. "Developing a multidimensional instrument to measure psychic distance stimuli," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 37(5), pages 578-602, September.
    2. Liu, Yong & Teichert, Thorsten & Rossi, Matti & Li, Hongxiu & Hu, Feng, 2017. "Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews," Tourism Management, Elsevier, vol. 59(C), pages 554-563.
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    Cited by:

    1. Nuno Antonio & Marisol B. Correia & Filipa Perdigão Ribeiro, 2020. "Exploring User-Generated Content for Improving Destination Knowledge: The Case of Two World Heritage Cities," Sustainability, MDPI, vol. 12(22), pages 1-19, November.
    2. Mellinas, Juan Pedro & Nicolau, Juan Luis, 2019. "Asymmetric effects of WiFi on overall satisfaction," Annals of Tourism Research, Elsevier, vol. 78(C), pages 1-1.
    3. Shuang Song & Hidenori Kawamura & Junichi Uchida & Hajime Saito, 2019. "Determining tourist satisfaction from travel reviews," Information Technology & Tourism, Springer, vol. 21(3), pages 337-367, September.
    4. Ferreira Ana & Correia Marisol B. & Renda Ana Isabel, 2024. "Systematic Literature Review on the Profile of Tourists in Four- and Five-star Hotels Based on Online Reviews," European Journal of Tourism, Hospitality and Recreation, Sciendo, vol. 14(1), pages 20-34.

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