Auditing Social Media Platforms: Public, Non-Public, and Alternative Data Access Methods under the DSA & GDPR for Public Interest Research
Workshop
Music Room
Thursday 22.05 — 17:20 - 18:40
Organising Institution
University of Lausanne
Switzerland
This workshop explores how official and alternative data access methods—provided by platforms and those developed independently by researchers and civil society—can be combined to audit systemic risks on very large online platforms. Participants will compare research APIs and transparency tools available under the Digital Services Act (DSA) with alternative approaches such as sockpuppet audits, analyzing strengths and limitations of each.
Through scenario-based simulations and interactive group role-play exercises, attendees will collaboratively design and debate audit strategies while confronting challenges like API restrictions, access barriers, platform compliance tactics, and legal uncertainties. Participants will gain hands-on experience with the SOAP (System for Observing and Analyzing Posts) tool, learning to simulate user interactions and collect algorithmic recommendation data. Throughout the session, ethical and legal considerations surrounding data collection and usage will be explored, equipping participants with practical skills to independently audit platform practices
Host
Konrad Kollnig
Maastricht University - Netherlands
Konrad Kollnig is assistant professor at the Law & Tech Lab of Maastricht University’s Law Faculty. He particularly focuses on the future of AI regulation (in leading the RegTech4AI project with 5 researchers), holding online platforms to account (in the co-leading the CoCoDa project across the UK, Switzerland and the EU) and building a more resilient digital infrastructure (in his latest book).
Luka Bekavac is a doctoral candidate at the University of St. Gallen. His research focuses on understanding and addressing the systemic risks posed by Very Large Online Platforms, combining methods from computer science, tech law and social sciences to study how platforms personalized recommender systems influence us, while developing tools to enhance transparency and accountability in their operation.
Simon Mayer is a Full Professor in Computer Science at the University of St. Gallen (HSG). He is fascinated by the integration of concepts and approaches from across the fields of pervasive computing, hypermedia, human-computer interaction, and embedded systems to realize ideal interfaces between machines and animals.