线上平台的线下偏见：Airbnb的多样性和同质性研究
Offline Biases in Online Platforms: a Study of Diversity and Homophily in Airbnb
摘要：
共享经济平台有多多样化？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，还是离线人类偏见的大规模在线聚合器？这类平台通常被描绘成易于访问的数字空间，参与者享有平等机会，但最近由于有报告称其用户存在歧视行为而受到抨击，并与加剧种族不平等的中产阶级化现象有关。在本文中，我们重点关注Airbnb共享经济平台，并分析其用户群在五个大城市的多样性。我们发现主要是年轻女性和白人。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房东和客人之间的同质性，异质性和回避行为。根据城市和财产类型，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。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
