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

Eunseo Choi, Emőke Ágnes Horvát*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationSocial Informatics - 11th International Conference, SocInfo 2019, Proceedings
EditorsIngmar Weber, Kareem M. Darwish, Claudia Wagner, Claudia Wagner, Fabian Flöck, Emilio Zagheni, Samin Aref, Laura Nelson
PublisherSpringer
Pages3-17
Number of pages15
ISBN (Print)9783030349707
DOIs
StatePublished - 2019
Event11th International Conference on Social Informatics, SocInfo 2019 - Doha, Qatar
Duration: Nov 18 2019Nov 21 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11864 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Social Informatics, SocInfo 2019
CountryQatar
CityDoha
Period11/18/1911/21/19

Keywords

  • Gender bias
  • Reputation systems
  • Sharing economy
  • Trust

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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