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Measurement and Analysis of the Reviews in Airbnb

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Abstract

Information and communications technologies have enabled the rise of the phenomenon named sharing economy, which represents activities between people, coordinated by online platforms, to obtain, provide, or share admission to goods and services. In hosting services of the sharing economy, it is common to take a personal contact between the host and invitee, and this may affect users' decision to practise negative reviews, as negative reviews can damage the offered services. To evaluate this issue, we collected reviews from two sharing economy platforms, Airbnb and Couchsurfing, and from one platform that works mostly with hotels (traditional economy), Booking.com, for some cities in Brazil and the Us. Through a sentiment analysis, nosotros plant that reviews in the sharing economy tend to exist considerably more positive than those in the traditional economy. This tin can represent a problem in those systems, every bit an experiment with volunteers performed in this written report suggests. In addition, we discuss how to exploit the results obtained to help improve users' determination making.

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Acknowledgements

This report was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. This piece of work is also partially supported by the project URBCOMP (Grant #403260 /2016-vii from National Council for Scientific and Technological Development agency - CNPq) and GoodWeb (Grant #2018/23011-1 from Sao Paulo Research Foundation - FAPESP). The authors would too similar to thank Marcelo Santos and all the volunteers for the valuable assistance in this study.

Funding

Grants that supported this study: CAPES - Finance Code 001, CNPq Grant #403260/2016-vii, FAPESP GoodWEB Project Grant #2018/23011-ane.

Author information

Writer notes

  1. Thiago H. Silva

    Present accost: University of Toronto, Toronto, Canada

Affiliations

  1. Universidade Tecnólogica Federal do Paraná, Curitiba, Brazil

    Gustavo Santos & Thiago H. Silva

  2. Universidade Federal practise Espirito Santo, Vitória, Brazil

    Vinicius F. South. Mota

  3. Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Fabrício Benevenuto

Corresponding author

Correspondence to Thiago H. Silva.

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The authors declare that they accept no conflict of interest.

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Appendices

Appendix ane: Topics of negative comments in Portuguese

This section presents the topic analysis for negative reviews written in Portuguese, following the same methodology presented in Sect. 5.v. The results in Table vi follow a similar design to the i observed English reviews.

Table 6 X latent topics from negative comments written in English language shared on Booking and Airbnb

Total size tabular array

Appendix 2: Simulation of score

Table seven shows some examples of score based on reviews and polarity of Airbnb. This helps us to take an idea on how each variable impacted score. In these examples, the score values ranged from five.09 (worst score) to 64.69 (best score).

Table 7 Examples of score based on reviews and polarity of Airbnb

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Cite this article

Santos, One thousand., Mota, V.F.S., Benevenuto, F. et al. Neutrality may matter: sentiment assay in reviews of Airbnb, Booking, and Couchsurfing in Brazil and USA. Soc. Netw. Anal. Min. 10, 45 (2020). https://doi.org/10.1007/s13278-020-00656-5

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  • DOI : https://doi.org/x.1007/s13278-020-00656-5

Keywords

  • Sentiment analysis
  • Text analysis
  • Reviews
  • Booking
  • Airbnb
  • Couchsurfing

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