Fighting bias with bias: How same-race endorsements reduce racial discrimination on Airbnb

Minsu Park*, Chao Yu*, Michael Macy*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Recent studies have documented racial discrimination in online interactions, mirroring the historic bias observed offline. The sharing economy is especially vulnerable due to greater dependence on mutual trust in sharing a ride, residence, or date with a stranger. These services rely on user recommendations to build trust, but the effects of these peer evaluations on racial bias are only beginning to be explored. Using data from Airbnb, we examine in-group preference for same-race hosts as well as same-race recommendations. The unexpected result is that these two manifestations of racial bias are offsetting, not reinforcing. White guests largely overcame their racial bias in host selection when hosts were endorsed by previous white guests. Moreover, we found no evidence of racial bias in the affective enthusiasm of endorsements, which suggests that the preference for same-race endorsements is motivated by the race of the recommender, not the content of the recommendation.

Original languageEnglish (US)
Article numbereadd2315
JournalScience Advances
Volume9
Issue number6
DOIs
StatePublished - Feb 10 2023

Funding

We greatly appreciate members of Cornell’s Social Dynamics Laboratory and New York University Abu Dhabi’s Social Research and Public Policy Writing Group for their helpful suggestions. M.M. acknowledges the U.S. National Science Foundation (SES 2049207 and SES 1756822) and the DARPA Ground Truth Program for their support during the time the research for this project was conducted.

ASJC Scopus subject areas

  • General

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