Offline biases in online platforms: a study of diversity and homophily in Airbnb
Offline biases in online platforms: a study of diversity and homophily in Airbnb
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DOI：
10.1140/epjds/s13688-019-0189-5
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发表时间：
2019-03-29
期刊：
影响因子：
3.6
通讯作者：
Capra, Licia
中科院分区：
文献类型：
--
作者：
Koh, Victoria;Li, Weihua;Capra, Licia
共享经济平台的多样性有多大？它们是公平的市场，所有参与者都在公平的竞争环境中运作，还是线下人类偏见的大规模在线聚集者？这类平台通常被描述为易于访问的数字空间，参与者获得平等机会，但最近由于有报告称其用户存在歧视行为，这些平台受到了抨击，并与加剧种族界限上先前存在的不平等的士绅化现象有关。本文以Airbnb共享经济平台为研究对象，分析了其在五个大城市的用户群差异性。我们发现它主要是年轻的、女性的和白人。值得注意的是，我们发现即使在种族构成多样化的城市也是如此。然后，我们介绍了一种基于网络统计分析的方法来量化Airbnb主机和客户之间的同形、异形和回避行为。根据城市和房产类型的不同，我们确实发现了与种族和性别有关的此类行为的信号。我们利用这些发现来提供平台设计建议，旨在揭露并可能减少我们发现的偏见，以支持共享经济平台更具包容性的增长。
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.