Peters, Y., & Weller, K. (2026). Little mentioning, moderate attention, great relevance: The quality of online platform data in the Digital Services Act. Platforms & Society, 3. https://doi.org/10.1177/29768624261438624
Summary
This paper examines how data quality is conceptualized and contested within the European Union’s Digital Services Act (DSA), specifically Article 40 and its Delegated Regulation, which govern researcher access to public and nonpublic data from Very Large Online Platforms. Through a mixed-methods analysis of the regulatory texts and 242 feedback entries submitted during two European Commission Call for Evidence periods, Peters and Weller show that data quality was largely absent from official EU documents but was pushed onto the agenda by academic and NGO stakeholders, who partially succeeded in embedding it into the final Delegated Regulation. Their central argument is that data quality should be understood not as a purely methodological construct but as a politically contested concept negotiated among researchers, platforms, and regulators.
Key Contributions
- First empirical analysis of how data quality is discursively constructed and contested within the DSA regulatory process.
- A typology of three stakeholder perspectives on platform data quality: research standard (academics), economic good (platforms), and regulatory perspective (EU institutions).
- Demonstrates Multiple Correspondence Analysis (MCA) as a tool for mapping discursive positions in platform governance debates.
- Bridges methodological data-quality literature with platform governance and platformization scholarship.
- Concrete policy recommendations: independent institutions for long-term quality assessment, benchmark datasets, and auditing mechanisms.
- An annotated dataset and reproducible code released publicly.
Methods
- Quantitative content analysis of 242 feedback entries (133 in period 1, 109 in period 2) from 214 unique organizations, with binary coding of general and intrinsic (accuracy, completeness, consistency) references to data quality; inter-coder reliability was high (Krippendorff’s α = 0.92, Holsti = 0.95).
- Multiple Correspondence Analysis (MCA) on four data-quality variables to construct a discursive “data quality space,” with stakeholder type as a supplementary variable.
- Hierarchical Clustering on Principal Components (HCPC) to identify four actor response-profile clusters.
- Thematic analysis (Braun & Clarke) of data-quality text passages, plus word-frequency analysis across the DSA, draft Delegated Regulation, and final Delegated Regulation. The analytic frame draws on Bourdieusian geometric data analysis.
Findings
- 38.79% of submitters referenced intrinsic data quality at least once; mentions rose in the second period (24.3% general references vs. 19.6% in the first).
- Academic/research institutions (35.98%) and NGOs (21.02%) were the most active submitters; 20.56% of submissions came from the USA, signalling transnational engagement.
- MCA’s first two dimensions explained 69.2% of inertia: Dimension 1 (44.3%) distinguished feedback periods; Dimension 2 (24.8%) distinguished mention vs. non-mention of data quality.
- NGOs and academics clustered as more likely to mention data quality; companies, business associations, and public authorities clustered as less likely.
- Of major platforms, only Meta and Snapchat explicitly mentioned data quality — Meta strategically inverted the argument, claiming low platform data quality rendered researcher access futile.
- Researchers most often cited completeness and accuracy, linking them to collection methods (APIs, donations, scraping) and calling for independent audits.
- Advocacy succeeded in adding data-quality language to Recitals 7 and 13 of the final Delegated Regulation, but failed to secure researcher rights to initiate mediation under Article 13.
Connections
This paper sits squarely in the DSA Article 40 data-access debate and connects to work on the mechanics and limits of that access regime, such as Rieder2026-pp and Rieder2025-ju. Its concern with platform-provided data quality and the “post-API age” resonates with studies of API and data-donation validity like Ohme2026-nv and with broader critical assessments of platform data reliability. Its regulatory-governance framing complements policy-oriented analyses of researcher access such as de-Vreese2026-zx and Bruns2026-yv.
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