Join us for an exciting talk by Dr. Philipp Lorez-Spreen on how to understand the complexity of the Digital Service Acts and how to engage with research data under this new framework.
European policymakers – pushed by academia and civil society – have acknowledged the need for researchers to access platform data and the value of the resulting studies to help with independent platform oversight in the public interest. Most prominently, lawmakers in the European Union included a data access provision for researchers in the Digital Services Act (DSA). This article (Article 40) could potentially provide a huge opportunity for researchers to better understand platforms and, ultimately, help independent regulators oversee platforms based on scientific evidence. Yet, despite the promises held by the DSA, many important open questions remain. Details on data access requests, the type of data to be requested, the timelines for full application and the communication exchanges between researchers, regulators and platforms will be hashed out over the coming months.
In this talk Dr. Philipp Lorenz-Spreen, network scientist at the Center for Adaptive Rationality of the Max Planck Institute for Human Development, will present the DSA’s Article 40 to provide researchers with a better understanding of who can request data for what type of research, how this process works and what open questions might be addressed in what way.
About the speaker:
Dr. Philipp Lorenz-Spreen is a network scientist at the Center for Adaptive Rationality of the Max Planck Institute for Human Development, Berlin. He is interested in how and why information spreads via social media, and more generally, in the impact of modern information systems on our society and on the public domain. To that end, he analyzes large data sets from social media and other sources. This allows quantitative access to human behavior at the societal level and across large time spans.
Dr. Lorenz-Spreen’s current research centers on the question of how individual choice environments can be changed to translate into positive collective effects of quality information distribution. He is experimentally testing ways to computationally extract meaningful cues for the quality of online information and make them more accessible to large numbers of users.
He completed his PhD on empirical methods and theoretical models for describing the dynamics of collective attention from online data sets at the Technische Universität Berlin. At the Ludwig-Maximilians-Universität in Munich, he studied physics, focusing on systems biophysics.
Contact person
- Huy Ngoc Dang, Manager of Data Science Lab & Programme Coordinator of Master of Data Science for Public Policy
