mlsanityData to 7 Oct 2026

The DSA's Blind Spot: Algorithmic Audit of Advertising and Minor Profiling on TikTok

arXiv 2603.05653 ↗First posted 5 Mar 2026cs.CY cs.AI cs.IRcited by 1

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Abstract (arXiv)

Adolescents spend an increasing amount of their time in digital environments where their still-developing cognitive capacities leave them unable to recognize or resist commercial persuasion. Article 28(2) of the DSA responds to this vulnerability by prohibiting profiling-based advertising to minors. However, the regulation's narrow definition of "advertisement" excludes current advertising practices including influencer paid partnerships and brand promotional content that serve functionally equivalent commercial purposes. We provide the first empirical evidence of how this definitional gap operates in practice through an algorithmic audit of TikTok. Our approach deploys sock-puppet accounts simulating a pair of minor and adult users with matching interest profiles. The content recommended to these users is automatically annotated, enabling systematic statistical analysis. Our findings reveal a stark regulatory paradox. TikTok demonstrates formal compliance with Article 28(2) by shielding minors from profiled formal advertisements, yet both disclosed and undisclosed ads exhibit significant profiling aligned with user interests (5-8 times stronger than for adult formal advertising). The strongest profiling emerges within undisclosed commercial content, where creators/brands fail to label paid partnership/promotional content and the platform neither corrects this omission nor prevents its personalized delivery to minors. These results demonstrate that minors remain exposed to algorithmically targeted commercial content through the same recommendation mechanisms the DSA seeks to constrain. We argue that protecting minors requires expanding the definition of advertisement in EU law to encompass influencer and brand promotional content, and ensuring that any such expansion is accompanied by a corresponding prohibition on profiling-based targeting of minors.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 73 references that are in the map. First posted on arXiv 5 Mar 2026.

Builds on

8 of 73 references.

References · 8

  1. 2019Auditing Radicalization Pathways on YouTubecited by 52
  2. 2022An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changescited by 15
  3. 2022Auditing YouTube's Recommendation Algorithm for Misinformation Filter Bubblescited by 7
  4. 2024WEIRD Audits? Research Trends, Linguistic and Geographical Disparities in the Algorithm Audits of Online Platforms -- A Systematic Literature Reviewcited by 3
  5. 2025Revisiting Algorithmic Audits of TikTok: Poor Reproducibility and Short-term Validity of Findingscited by 2
  6. 2024Auditing for Bias in Ad Delivery Using Inferred Demographic Attributescited by 1
  7. 2025The EU Digital Services Act: what does it mean for online advertising and adtech?cited by 1
  8. 2026Beyond the Checkbox: Strengthening DSA Compliance Through Social Media Algorithmic Auditingcited by 1

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Citing papers per year: 2026: 1.

1 paper.