A Year of the DSA Transparency Database: What it (Does Not) Reveal About Platform Moderation During the 2024 European Parliament Election
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Abstract (arXiv)
Social media platforms face heightened risks during major political events; yet, how platforms adapt their moderation practices in response remains unclear. The Digital Services Act Transparency Database offers an unprecedented opportunity to systematically study content moderation at scale, enabling researchers and policymakers to assess platforms' compliance and effectiveness. Herein, we analyze 1.58 billion self-reported moderation actions taken by eight large social media platforms during an extended period of eight months surrounding the 2024 European Parliament elections. Our findings reveal a lack of adaptation in moderation strategies, as platforms did not exhibit significant changes in their enforcement behaviors surrounding the elections. This raises concerns about whether platforms adapted their moderation practices at all, or if structural limitations of the database concealed possible adjustments. Moreover, we found that noted transparency and accountability issues persist nearly a year after initial concerns were raised. These results highlight the limitations of current self-regulatory approaches and underscore the need for stronger enforcement and data access mechanisms to ensure that online platforms uphold their responsibility in safeguarding democratic processes.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Apr 2025.
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Citing papers per year: 2025: 2; 2026: 3.
5 papers.
- 2026Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalizationcited by 1
- 2025Defining, Understanding, and Detecting Online Toxicity: Challenges and Machine Learning Approachescited by 0
- 2025Quantifying Feature Importance for Online Content Moderationcited by 0
- 2026Contextualized Counterspeech Can Be More Persuasive Than Generic Counterspeechcited by 0
- 2026Characterizing Bluesky Content Moderation Service: From Automation of Service to Landscape of Harmscited by 0
- 2026Characterizing Bluesky Content Moderation Service: From Automation of Service to Landscape of Harms10 Sep 2026
- 2026Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization9 Sep 2026
- 2026Contextualized Counterspeech Can Be More Persuasive Than Generic Counterspeech28 Jul 2026
- 2025Quantifying Feature Importance for Online Content Moderation22 Oct 2025
- 2025Defining, Understanding, and Detecting Online Toxicity: Challenges and Machine Learning Approaches14 Sep 2025