# Turning Trust to Transactions: Tracking Affiliate Marketing and FTC Compliance in YouTube's Influencer Economy

arXiv: https://arxiv.org/abs/2603.04383 · HTML: https://mlsanity.com/paper/2603.04383/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 81 references that are in the map.
- First posted on arXiv 4 Mar 2026.

## Builds on (most cited first, 11 of 11)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Datasheets for Datasets](https://mlsanity.com/paper/1803.09010/) (2018)
- [Lost in Moderation: How Commercial Content Moderation APIs Over- and Under-Moderate Group-Targeted Hate Speech and Linguistic Variations](https://mlsanity.com/paper/2503.01623/) (2025)
- [An Empirical Study of Affiliate Marketing Disclosures on YouTube and Pinterest](https://mlsanity.com/paper/1803.08488/) (2018)
- [Across Platforms and Languages: Dutch Influencers and Legal Disclosures on Instagram, YouTube and TikTok](https://mlsanity.com/paper/2407.12451/) (2024)
- [Influencer Self-Disclosure Practices on Instagram: A Multi-Country Longitudinal Study](https://mlsanity.com/paper/2407.09202/) (2024)
- [Conspiracy Brokers: Understanding the Monetization of YouTube Conspiracy Theories](https://mlsanity.com/paper/2205.15943/) (2022)
- [The Monetisation of Toxicity: Analysing YouTube Content Creators and Controversy-Driven Engagement](https://mlsanity.com/paper/2408.00534/) (2024)
- [Characterizing Alternative Monetization Strategies on YouTube](https://mlsanity.com/paper/2203.10143/) (2022)
- [The Inventory is Dark and Full of Misinformation: Understanding the Abuse of Ad Inventory Pooling in the Ad-Tech Supply Chain](https://mlsanity.com/paper/2210.06654/) (2022)
- [Towards Multi-Stakeholder Vulnerability Notifications in the Ad-Tech Supply Chain](https://mlsanity.com/paper/2406.06958/) (2024)

## Abstract (arXiv)

YouTube has evolved into a powerful platform where creators monetize their influence through affiliate marketing, raising concerns about transparency and ethics, especially when creators fail to disclose their affiliate relationships. Although regulatory agencies like the US Federal Trade Commission (FTC) have issued guidelines to address these issues, non-compliance and consumer harm persist, and the extent of these problems remains unclear. In this paper, we introduce tools, developed with insights from recent advances in Web measurement and NLP research, to examine the state of the affiliate marketing ecosystem on YouTube. We apply these tools to a 10-year dataset of 2 million videos from nearly 540,000 creators, analyzing the prevalence of affiliate marketing on YouTube and the rates of non-compliant behavior. Our findings reveal that affiliate links are widespread, yet disclosure compliance remains low, with most videos failing to meet FTC standards. Furthermore, we analyze the effects of different stakeholders in improving disclosure behavior. Our study suggests that the platform is highly associated with improved compliance through standardized disclosure features. We recommend that regulators and affiliate partners collaborate with platforms to enhance transparency, accountability, and trust in the influencer economy.