Algorithmic Public Service Media Content Recommendation

Beskrivelse

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 project is conducted in collaboration with Hans Bredow Institute for Media Research at Universität Hamburg, as part of the "Algorithmed Public Spheres" research project
StatusIgangværende
Effektiv start/slut dato19/10/201530/06/2020

Emneord

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