Element 68Element 45Element 44Element 63Element 64Element 43Element 41Element 46Element 47Element 69Element 76Element 62Element 61Element 81Element 82Element 50Element 52Element 79Element 79Element 7Element 8Element 73Element 74Element 17Element 16Element 75Element 13Element 12Element 14Element 15Element 31Element 32Element 59Element 58Element 71Element 70Element 88Element 88Element 56Element 57Element 54Element 55Element 18Element 20Element 23Element 65Element 21Element 22iconsiconsElement 83iconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsElement 84iconsiconsElement 36Element 35Element 1Element 27Element 28Element 30Element 29Element 24Element 25Element 2Element 1Element 66
Algorithmic Recommendations. Functionality, Meaning and Peculiarities for Public Service Broadcasters

Algorithmic Recommendations. Functionality, Meaning and Peculiarities for Public Service Broadcasters

The increasing significance of digitally networked media has fundamentally changed the structures of the social public sphere. An essential part of this change is that the selection, processing and presentation of information is no longer carried out by the editorial offices of journalists and publicists alone.

Especially with search engines like Google or social media intermediaries like Facebook, YouTube or Twitter, algorithmic selection and recommendation systems perform the indispensable task of selecting from the wealth of information and content available to users. An essential performance promise of algorithmic systems in this context is the “personalisation” of information offers, so the most individual compilation of relevant, interesting and otherwise suitable recommendations. For some years now, however, it has also been critically discussed whether algorithmic personalisation may contribute to social fragmentation and polarization, using keywords such as "filter bubble" or “echo chamber”.

This development is forcing media organisations to consider strategically to what extent algorithmic recommendation systems should be part of their own journalistic activity, meaning to what extent they should take the side of (or take the place of) journalistic selection and compilation of information. For public service broadcasters, their constitutional mandate raises special questions, such as the balance between personalisation on the one hand and basic provision on socially relevant issues on the other hand.

Against this backdrop, the Hans-Bredow-Institut has produced a White Paper for the MDR summarises the main characteristics and principles of algorithmic recommendation systems and discusses their consequences for public service offerings.

The White Paper has been published as 'Working Paper of the Hans-Bredow-Institut, No. 45' (in German):

Jan-Hinrik Schmidt / Jannick Sørensen / Stephan Dreyer / Uwe Hasebrink (2018): Algorithmische Empfehlungen. Funktionsweise, Bedeutung und Besonderheiten für öffentlich-rechtliche Rundfunkanstalten [Algorithmic Recommendations - Functionality, Meaning and Peculiarities for Public Service Broadcasters]. Hamburg: Verlag Hans-Bredow-Institut, September 2018 (Working Papers of the Hans-Bredow-Instituts, No. 45) (pdf)

A short version of the white paper has been published as article in the journal MediaPerspektiven (in German):

Jan-Hinrik Schmidt / Jannick Sørensen / Stephan Dreyer / Uwe Hasebrink (2018): Wie können Empfehlungssysteme zur Vielfalt von Medieninhalten beitragen? Perspektiven für öffentlich-rechtliche Rundfunkanstalten. In: Media Perspektiven, 11/2018, S. 522-531. (pdf)
 
show more

Project Description

Photo by Clint Adair on Unsplash

Project Information

Overview

Duration: 2017-2018

Research programme:
RP1 - Transformation of Public Communication

Third party

Mitteldeutscher Rundfunk (mdr)

Cooperation Partner

Jannick Kirk Sørensen

Contact person

Dr. Jan-Hinrik Schmidt
Senior Researcher Digital Interactive Media & Political Communication

Dr. Jan-Hinrik Schmidt

Leibniz-Institut für Medienforschung | Hans-Bredow-Institut (HBI)
Rothenbaumchaussee 36
20148 Hamburg

Tel. +49 (0)40 45 02 17-83
Fax +49 (0)40 45 02 17-77

Send Mail

MAYBE YOU ARE ALSO INTERESTED IN THESE TOPICS?

Newsletter

Subscribe to our newsletter and receive the Institute's latest news via email.

SUBSCRIBE!