# Across Platforms and Languages: Dutch Influencers and Legal Disclosures on Instagram, YouTube and TikTok

arXiv: https://arxiv.org/abs/2407.12451 · HTML: https://mlsanity.com/paper/2407.12451/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 18 references that are in the map.
- First posted on arXiv 17 Jul 2024.

## Builds on (most cited first, 4 of 4)

- [An Empirical Study of Affiliate Marketing Disclosures on YouTube and Pinterest](https://mlsanity.com/paper/1803.08488/) (2018)
- [Closing the Loop: Testing ChatGPT to Generate Model Explanations to Improve Human Labelling of Sponsored Content on Social Media](https://mlsanity.com/paper/2306.05115/) (2023)
- [Characterising and Detecting Sponsored Influencer Posts on Instagram](https://mlsanity.com/paper/2011.05757/) (2020)
- [InstaSynth: Opportunities and Challenges in Generating Synthetic Instagram Data with ChatGPT for Sponsored Content Detection](https://mlsanity.com/paper/2403.15214/) (2024)

## Built on by (most cited first, 5 of 5)

- [Evaluating LLM-Generated Legal Explanations for Regulatory Compliance in Social Media Influencer Marketing](https://mlsanity.com/paper/2510.08111/) (2025)
- [Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models](https://mlsanity.com/paper/2505.02858/) (2025)
- [Turning Trust to Transactions: Tracking Affiliate Marketing and FTC Compliance in YouTube's Influencer Economy](https://mlsanity.com/paper/2603.04383/) (2026)
- [ChildSafeAds Shared Task 2026: Commercial Content in Child-Facing YouTube Videos](https://mlsanity.com/paper/2608.19165/) (2026)
- [N"urnberg NLP at ChildSafeAds 2026: Structurally Dissimilar Voter Ensembles under Four Levels of Data Access](https://mlsanity.com/paper/2609.34986/) (2026)

## Abstract (arXiv)

Content monetization on social media fuels a growing influencer economy. Influencer marketing remains largely undisclosed or inappropriately disclosed on social media. Non-disclosure issues have become a priority for national and supranational authorities worldwide, who are starting to impose increasingly harsher sanctions on them. This paper proposes a transparent methodology for measuring whether and how influencers comply with disclosures based on legal standards. We introduce a novel distinction between disclosures that are legally sufficient (green) and legally insufficient (yellow). We apply this methodology to an original dataset reflecting the content of 150 Dutch influencers publicly registered with the Dutch Media Authority based on recently introduced registration obligations. The dataset consists of 292,315 posts and is multi-language (English and Dutch) and cross-platform (Instagram, YouTube and TikTok). We find that influencer marketing remains generally underdisclosed on social media, and that bigger influencers are not necessarily more compliant with disclosure standards.