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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Benefits of Diverse News Recommendations for Democracy: A User Study
Organization Unit
  • Lucien Heitz
  • Juliane A. Lischka
  • Alena Birrer
  • Bibek Paudel
  • Suzanne Tolmeijer
  • Laura Laugwitz
  • Abraham Bernstein
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
Journal Title Digital Journalism
Publisher Taylor and Francis
Geographical Reach international
ISSN 2167-0811
Volume 10
Number 10
Page Range 1710 - 1730
Date 2022
Abstract Text News recommender systems provide a technological architecture that helps shaping public discourse. Following a normative approach to news recommender system design, we test utility and external effects of a diversity-aware news recommender algorithm. In an experimental study using a custom-built news app, we show that diversity-optimized recommendations (1) perform similar to methods optimizing for user preferences regarding user utility, (2) that diverse news recommendations are related to a higher tolerance for opposing views, especially for politically conservative users, and (3) that diverse news recommender systems may nudge users towards preferring news with differing or even opposing views. We conclude that diverse news recommendations can have a depolarizing capacity for democratic societies.
Official URL
Digital Object Identifier 10.1080/21670811.2021.2021804
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