Algorithmic Public Service Media Content Recommendation



This project examines the potentials and implications of the possible use of algorithmic recommender systems on public service media content. A main question is whether such algorithmic systems should consider diversity in its recommendations as diversity traditionally is understood in a media political context, or systems should operate as commercial content recommender systems. Should the PSB / PSM remit and the policy goals in public service media contracts (and similar) be reflected in the construction and fine-tuning of the algorithms, or should they reflect user-demands only?

The initial part of the project was conducted in collaboration with Hans Bredow Institute for Media Research at Universität Hamburg, as part of the "Algorithmed Public Spheres" research project
Effektiv start/slut dato19/10/201530/12/2022


  • Public Service Broadcast
  • public service media
  • recommender systems
  • user profiles
  • filter bubble
  • diversitet
  • Diversity
  • media policy
  • media distribution
  • algorithmic content recommendation


Udforsk forskningsemnerne, som dette projekt berører. Disse etiketter er oprettet på grundlag af de underliggende bevillinger/legater. Sammen danner de et unikt fingerprint.