Understanding the Privacy Practices of Political Campaigns: A Perspective from the 2020 US Election Websites
Kaushal Kafle, Prianka Mandal, Kapil Singh, Benjamin Andow, Adwait Nadkarni
Abstract
Political campaigns are known to collect private user data, whether for building voter profiles, engaging with volunteers, or for soliciting donations. However, as such campaigns are classified as nonprofit in the United States (U.S.), their privacy practices have not received the same level of scrutiny as those of for-profit enterprises. This paper presents the Polityzer framework to evaluate the privacy posture of political campaign websites, and uses it to analyze 2060 campaign websites active during the U.S. election of November 2020. Our analysis leads to 20 key findings that demonstrate gaps in the privacy postures of political campaigns. For instance, we find that campaigns collect extensive private data they are not required to by the Federal Election Commission (FEC), and a vast majority do not provide any form of privacy disclosure. When disclosures are provided, they are often incomplete. We also found that campaigns may be inadvertently sharing data with other campaigns through common fundraising platforms, without disclosing such sharing. Reporting the lack of privacy disclosure to the respective campaigns yields further insights into the rationale behind their security posture. Finally, we discuss ways in which our results could enable future research, inform emerging privacy regulations, and transform user behavior regarding data privacy in this critical context.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers3
- Breaking the Illusion: Automated Reasoning of GDPR Consent ViolationsYing Li, Wenjun Qiu, Faysal Hossain Shezan, Kunlin Cai et al.S&P 2026 · 1 citation
- Evaluating Privacy Policies under Modern Privacy Laws At Scale: An LLM-Based Automated ApproachQinge Xie, Karthik Ramakrishnan, Frank LiUSENIX Security 2025
- PrivAudit: A Dual-Lens Auditing Framework for Website Privacy Practices under the CCPAMohamed Moustafa Dawoud, Riya Aggarwal, Likith Rahul Krishnamurthy, Ram Sundara RamanCCS 2026
Builds on8
- Online Tracking: A 1-million-site Measurement and AnalysisSteven Englehardt, Arvind NarayananCCS 2016 · 798 citations
- TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and TimeFeargus Pendlebury, Fabio Pierazzi, Roberto Jordaney, Johannes Kinder et al.USENIX Security 2019 · 441 citations
- Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep LearningHamza Harkous, Kassem Fawaz, Rémi Lebret, Florian Schaub et al.USENIX Security 2018 · 400 citations
- Automated Analysis of Privacy Requirements for Mobile AppsSebastian Zimmeck, Ziqi Wang, Lieyong Zou, Roger Iyengar et al.NDSS 2017 · 255 citations
- PolicyLint: Investigating Internal Privacy Policy Contradictions on Google PlayBenjamin Andow, Samin Yaseer Mahmud, Wenyu Wang, Justin Whitaker et al.USENIX Security 2019 · 185 citations
Related papers
- An Audit of Facebook's Political Ad Policy EnforcementVictor Le Pochat, Laura Edelson, Tom van Goethem, Wouter Joosen et al.USENIX Security 2022
- "Why wouldn't someone think of democracy as a target?": Security practices & challenges of people involved with U.S. political campaignsSunny Consolvo, Patrick Gage Kelley, Tara Matthews, Kurt Thomas et al.USENIX Security 2021 · 15 citations
- Understanding the Complexity of Detecting Political AdsVera Sosnovik, Oana GogaWWW 2021 · 32 citations
- Automating Website Registration for Studying GDPR ComplianceKarel Kubicek, Jakob Merane, Ahmed Bouhoula, David A. BasinWWW 2024 · 9 citations
- A Security Analysis of the Facebook Ad LibraryLaura Edelson, Tobias Lauinger, Damon McCoyS&P 2020 · 43 citations
