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

Haoyang Gui, Thales Bertaglia, Catalina Goanta, Sybe de Vries, Gerasimos Spanakis

TL;DR

This study tackles the persistent problem of undisclosed influencer marketing by aligning measurement with jurisdiction-specific legal standards in the Netherlands. It develops a transparent methodology and a green/yellow disclosure taxonomy, applied to a multilingual, cross-platform dataset of 150 Dutch influencers registered with the Dutch Media Authority, across Instagram, YouTube, and TikTok with 292,315 posts. It also operationalizes affiliate marketing detection and constructs an AM sub-dataset to benchmark disclosure practices. The findings reveal pronounced under-disclosure across platforms and languages, with larger influencers not consistently more compliant, highlighting regulatory gaps and offering a practical framework for regulators, platforms, and researchers.

Abstract

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.

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

TL;DR

This study tackles the persistent problem of undisclosed influencer marketing by aligning measurement with jurisdiction-specific legal standards in the Netherlands. It develops a transparent methodology and a green/yellow disclosure taxonomy, applied to a multilingual, cross-platform dataset of 150 Dutch influencers registered with the Dutch Media Authority, across Instagram, YouTube, and TikTok with 292,315 posts. It also operationalizes affiliate marketing detection and constructs an AM sub-dataset to benchmark disclosure practices. The findings reveal pronounced under-disclosure across platforms and languages, with larger influencers not consistently more compliant, highlighting regulatory gaps and offering a practical framework for regulators, platforms, and researchers.

Abstract

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.
Paper Structure (8 sections, 4 figures, 2 tables)

This paper contains 8 sections, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Content Monetization and Legal Disclosures
  4. Methodology
  5. Findings
  6. Discussion and Future Research
  7. Limitations
  8. Acknowledgments

Figures (4)

  • Figure 1: Instagram disclosure composition.
  • Figure 2: Top 5 accounts with the most disclosed AM on each platform and the corresponding disclosure rate for their own AM.
  • Figure 3: Box plots of engagement for AM by different disclosure word positions in each influencer category
  • Figure 4: Engagement by different disclosure strategies of AM on Instagram