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Automated Transparency: A Legal and Empirical Analysis of the Digital Services Act Transparency Database

Rishabh Kaushal, Jacob van de Kerkhof, Catalina Goanta, Gerasimos Spanakis, Adriana Iamnitchi

TL;DR

This study evaluates the EU Digital Services Act's automated transparency mechanism by examining the SoRs in the DSA Transparency Database. Using a legal doctrinal framework alongside empirical data analysis of a November 2023 snapshot (131 million SoRs across all VLOPs), the authors assess how the database structure and submissions align with Articles 17 and 24(5) and what this means for actual transparency and compliance. They find tangible transparency gains in standardized data, but significant discretion remains due to conditional/missing fields and a heavy reliance on ToS-based grounds rather than legal illegality. The work highlights that while automated transparency is a powerful step toward accountability, it currently falls short of fully realizing the DSA's promises, underscoring the need for complementary transparency mechanisms and ongoing multidisciplinary scrutiny.

Abstract

The Digital Services Act (DSA) is a much awaited platforms liability reform in the European Union that was adopted on 1 November 2022 with the ambition to set a global example in terms of accountability and transparency. Among other obligations, the DSA emphasizes the need for online platforms to report on their content moderation decisions (`statements of reasons' - SoRs), which is a novel transparency mechanism we refer to as automated transparency in this study. SoRs are currently made available in the DSA Transparency Database, launched by the European Commission in September 2023. The DSA Transparency Database marks a historical achievement in platform governance, and allows investigations about the actual transparency gains, both at structure level as well as at the level of platform compliance. This study aims to understand whether the Transparency Database helps the DSA to live up to its transparency promises. We use legal and empirical arguments to show that while there are some transparency gains, compliance remains problematic, as the current database structure allows for a lot of discretion from platforms in terms of transparency practices. In our empirical study, we analyze a representative sample of the Transparency Database (131m SoRs) submitted in November 2023, to characterise and evaluate platform content moderation practices.

Automated Transparency: A Legal and Empirical Analysis of the Digital Services Act Transparency Database

TL;DR

This study evaluates the EU Digital Services Act's automated transparency mechanism by examining the SoRs in the DSA Transparency Database. Using a legal doctrinal framework alongside empirical data analysis of a November 2023 snapshot (131 million SoRs across all VLOPs), the authors assess how the database structure and submissions align with Articles 17 and 24(5) and what this means for actual transparency and compliance. They find tangible transparency gains in standardized data, but significant discretion remains due to conditional/missing fields and a heavy reliance on ToS-based grounds rather than legal illegality. The work highlights that while automated transparency is a powerful step toward accountability, it currently falls short of fully realizing the DSA's promises, underscoring the need for complementary transparency mechanisms and ongoing multidisciplinary scrutiny.

Abstract

The Digital Services Act (DSA) is a much awaited platforms liability reform in the European Union that was adopted on 1 November 2022 with the ambition to set a global example in terms of accountability and transparency. Among other obligations, the DSA emphasizes the need for online platforms to report on their content moderation decisions (`statements of reasons' - SoRs), which is a novel transparency mechanism we refer to as automated transparency in this study. SoRs are currently made available in the DSA Transparency Database, launched by the European Commission in September 2023. The DSA Transparency Database marks a historical achievement in platform governance, and allows investigations about the actual transparency gains, both at structure level as well as at the level of platform compliance. This study aims to understand whether the Transparency Database helps the DSA to live up to its transparency promises. We use legal and empirical arguments to show that while there are some transparency gains, compliance remains problematic, as the current database structure allows for a lot of discretion from platforms in terms of transparency practices. In our empirical study, we analyze a representative sample of the Transparency Database (131m SoRs) submitted in November 2023, to characterise and evaluate platform content moderation practices.
Paper Structure (16 sections, 4 figures, 2 tables)

This paper contains 16 sections, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Prior work and contributions of the present study
  3. Dataset
  4. Statements of Reasons (SoRs) and DSA Compliance
  5. SoRs requirements
  6. SoRs template and its compliance with the DSA
  7. Platform Practices and early DSA compliance
  8. Who is Reporting: VLOPs
  9. How Moderation Decisions and Detection are Done
  10. Why: Reasons for Moderation
  11. How Platforms Sanction: What Moderation Actions are Reported
  12. Where Content is Moderated: Language and Territorial Scope
  13. When SoRs are Submitted ("Without Undue Delay")
  14. Conclusion: Does the DSA's automated transparency rise to its promise?
  15. Appendices
  16. ...and 1 more sections

Figures (4)

  • Figure 1: Fraction of SORs per day submitted by each VLOP.
  • Figure 2: Distribution of $automated\_detection$ and $automated\_decision$ in SoRs.
  • Figure 3: Moderation and upload delay for content posted before and after the launch of the Transparency database.
  • Figure 4: Cumulative distribution function of the moderation delay (time between content posting and moderation decision) and upload delay (time between moderation decision and reporting to the Transparency Database) of content posted after the database launch.