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International Conference on Social Informatics

SocInfo 2019: Social Informatics pp 3–17Cite as

Airbnb’s Reputation System and Gender Differences Among Guests: Evidence from Large-Scale Data Analysis and a Controlled Experiment

Part of the Lecture Notes in Computer Science book series (LNISA,volume 11864)

Abstract

Sharing economy platforms are rapidly scaling up by reaching increasingly diverse demographics. However, this expansion comes with great difficulties in adequately identifying and responding to everyone’s needs. In this paper, we study gender-related behaviors of guests on the currently most prominent home-sharing platform, Airbnb. While our results confirm the efficacy of Airbnb’s reputation system, we also find that the level of trust and participation on the platform varies by gender. In particular, female solo travelers are more likely to be conscious of review sentiment and choose more often female hosts than male solo travelers. Our findings are obtained by combining exploratory data analysis with large-scale experiments and call for further studies on the usage of sharing economy platforms among subpopulations, informing and improving both policy and practice in these growing online environments.

Keywords

  • Sharing economy
  • Reputation systems
  • Trust
  • Gender bias

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Acknowledgements

The authors would like to thank Joshua Becker and Johannes Wachs for their feedback. We are also grateful to all the anonymous Mechanical Turk participants for their input to the presented experimental studies (IRB: STU00207726). This work was supported in part by a Northwestern Undergraduate Summer Research grant and the U.S. National Science Foundation (IIS-1755873).

Author information

Authors and Affiliations

  1. Northwestern University, Evanston, IL, 60208, USA

    Eunseo Choi & Emőke-Ágnes Horvát

Authors
  1. Eunseo Choi
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  2. Emőke-Ágnes Horvát
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Corresponding author

Correspondence to Emőke-Ágnes Horvát .

Editor information

Editors and Affiliations

  1. Qatar Computing Research Institute, Doha, Qatar

    Ingmar Weber

  2. Qatar Computing Research Institute, Doha, Qatar

    Kareem M. Darwish

  3. University of Koblenz-Landau, Koblenz, Germany

    Claudia Wagner

  4. Max Planck Institute for Demographic Research, Rostock, Germany

    Emilio Zagheni

  5. Northeastern University, Boston, MA, USA

    Laura Nelson

  6. Max Planck Institute for Demographic Research, Rostock, Germany

    Samin Aref

  7. GESIS-Leibniz Institute for the Social Sciences, Cologne, Germany

    Fabian Flöck

A Appendix

A Appendix

Table 2. Basic statistics of host–reviewer networks built for NYC, LA, and Chicago.
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Fig. 3.
figure 3

Degree distributions of networks built for NYC, LA, and Chicago. Bipartite networks connect each host having a listing in the considered region with every guest who left a review on their profile. The number of reviews written by guests and the number of reviews obtained by hosts show that, in all but one case, male guests write and male hosts receive significantly more reviews.

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Choi, E., Horvát, EÁ. (2019). Airbnb’s Reputation System and Gender Differences Among Guests: Evidence from Large-Scale Data Analysis and a Controlled Experiment. In: , et al. Social Informatics. SocInfo 2019. Lecture Notes in Computer Science(), vol 11864. Springer, Cham. https://doi.org/10.1007/978-3-030-34971-4_1

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  • DOI: https://doi.org/10.1007/978-3-030-34971-4_1

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