Detailed targeting of advertisements has long been one of the core offerings of online platforms. Unfortunately, malicious advertisers have frequently abused such targeting features, with results that range from violating civil rights laws to driving division, polarization, and even social unrest. Platforms have often attempted to mitigate this behavior by removing targeting attributes deemed problematic, such as inferred political leaning, religion, or ethnicity. In this work, we examine the effectiveness of these mitigations by collecting data from political ads placed on Facebook in the lead up to the 2022 U.S. midterm elections. We show that major political advertisers circumvented these mitigations by targeting proxy attributes: seemingly innocuous targeting criteria that closely correspond to political and racial divides in American society. We introduce novel methods for directly measuring the skew of various targeting criteria to quantify their effectiveness as proxies, and then examine the scale at which those attributes are used. Our findings have crucial implications for the ongoing discussion on the regulation of political advertising and emphasize the urgency for increased transparency.

翻译：广告的精细定向长期以来一直是网络平台的核心功能之一。然而，恶意广告主频繁滥用此类定向功能，其后果从违反民权法到加剧社会分裂、两极分化乃至社会动荡不等。平台通常试图通过移除被认为有问题的定向属性（如推断的政治倾向、宗教或种族）来缓解此类行为。在本研究中，我们通过收集2022年美国中期选举前在Facebook上投放的政治广告数据，检验了这些缓解措施的有效性。我们发现，主要政治广告主通过定向代理属性规避了这些措施：这些看似无害的定向标准与美国社会的政治和种族分歧高度对应。我们提出了直接测量各类定向标准偏斜度的新方法，以量化其作为代理属性的有效性，进而考察这些属性的使用规模。我们的研究结果对当前关于政治广告监管的讨论具有重要启示，并强调了提高透明度的紧迫性。