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Airbnb or Hotel?: A Comparative Study on the Sentiment of Airbnb Guests in Sydney – Text Analysis Based on Big Data

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  • Zhiyong Li

    (School of Tourism, Sichuan University, China)

  • Honglin Chen

    (School of Tourism, Sichuan University, China)

  • Xia Huang

    (School of Tourism, Sichuan University, China)

Abstract

Advances in information technology have hugely influenced the tourism industry. Many tourists can generate and share their travel tips through social media, and people consult online reviews before making travel arrangements because they could access these sources of information easily. Either positive or negative reviews could increase consumer awareness of Airbnb. Using the approach of text mining and sentiment analysis, examining whether guests' emotions are positive or negative, this study investigates the attributes that influence Airbnb consumers' experiences compared with their previous hotel experiences by analysing big data of guests' online reviews. Findings reveal that the factors of guests' positive sentiment are the atmosphere, flexibility, special amenities, and humanized service; the factors of guests' negative sentiment are not value for money, have to clean the room before leaving, sharing amenities and space with strangers, disturbed by hosts' noisy recreational activities, and troubled by hosts' requesting good reviews.

Suggested Citation

  • Zhiyong Li & Honglin Chen & Xia Huang, 2020. "Airbnb or Hotel?: A Comparative Study on the Sentiment of Airbnb Guests in Sydney – Text Analysis Based on Big Data," International Journal of Tourism and Hospitality Management in the Digital Age (IJTHMDA), IGI Global, vol. 4(2), pages 1-10, July.
    • Handle: RePEc:igg:jthmda:v:4:y:2020:i:2:p:1-10
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