Algorithmic content curation, particularly in the context of news, has received plenty of attention, both academically and publicly. Theoretical expectations of individualized and biased news coverages or spiral processes of public-opinion (mis-)perceptions are fueled by catchy buzzwords, uncooperative intermediaries, and the need for more methodologically adequate empirical evidence. Drawing on a variety of methodologial enquiries into algorithmically curated media environments, such as agent-based testing and computational observation, this presentation will first provide an overview of the empirical and methodological status quo. Second, it will formulate various theses as a starting point for a subsequent open discussion on how the field could and/or should move on.

Haim, M. (3/2019). Personalized and polarized? Reflections on researching algorithmic content curation. Invited presentation at the Amsterdam School of Communication Research (ASCoR), Amsterdam. (content_copy)