On the Use of Proxies in Political Ad Targeting

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.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2024-11-07
DOI
https://doi.org/10.1145/3686917
Citations
1
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
0.35
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article

On the Use of Proxies in Political Ad Targeting

Aleksandra Korolova, Piotr Sapieżyński, Levi Kaplan, Alan Mislove
1 citations
Proceedings of the ACM on Human-Computer Interaction
Hate Speech and Cyberbullying Detection
0.35
article

On the Use of Proxies in Political Ad Targeting

Aleksandra Korolova, Piotr Sapieżyński, Levi Kaplan, Alan Mislove
article en
1 citations

Abstract

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.

Proceedings of the ACM on Human-Computer InteractionVol. 8(CSCW2)
Northeastern University (US), Princeton University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 32%
Hate Speech and Cyberbullying Detection
0.35
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On the Use of Proxies in Political Ad Targeting — Aleksandra Korolova, Piotr Sapieżyński, et al. · Proceedings of the ACM on Human-Computer Interaction (2024) | TGRS Research Map | TGRS