Title: Offline Biases in Online Platforms: a Study of Diversity and Homophily in Airbnb,
Abstract: How diverse are sharing economy platforms? Are they fair marketplaces, where
all participants operate on a level playing field, or are they large-scale
online aggregators of offline human biases? Often portrayed as easy-to-access
digital spaces whose participants receive equal opportunities, such platforms
have recently come under fire due to reports of discriminatory behaviours among
their users, and have been associated with gentrification phenomena that
exacerbate preexisting inequalities along racial lines. In this paper, we focus
on the Airbnb sharing economy platform, and analyse the diversity of its user
base across five large cities. We find it to be predominantly young, female,
and white. Notably, we find this to be true even in cities with a diverse
racial composition. We then introduce a method based on the statistical
analysis of networks to quantify behaviours of homophily, heterophily and
avoidance between Airbnb hosts and guests. Depending on cities and property
types, we do find signals of such behaviours relating both to race and gender.
We use these findings to provide platform design recommendations, aimed at
exposing and possibly reducing the biases we detect, in support of a more
inclusive growth of sharing economy platforms.