Burst of the Filter Bubble?

@article{Haim2018BurstOT,
  title={Burst of the Filter Bubble?},
  author={Mario Haim and Andreas Graefe and Hans-Bernd Brosius},
  journal={Digital Journalism},
  year={2018},
  volume={6},
  pages={330 - 343}
}
In offering personalized content geared toward users’ individual interests, recommender systems are assumed to reduce news diversity and thus lead to partial information blindness (i.e., filter bubbles). We conducted two exploratory studies to test the effect of both implicit and explicit personalization on the content and source diversity of Google News. Except for small effects of implicit personalization on content diversity, we found no support for the filter-bubble hypothesis. We did… 
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Personalization of News
  • Neil Thurman
  • Computer Science
    The International Encyclopedia of Journalism Studies
  • 2019
TLDR
It may be that traditional news providers, more so than social networks, will provide—within an increasingly personalized information environment—the common set of experiences and exposure to challenging viewpoints required in well functioning systems of free expression.
Search as News Curator: The Role of Google in Shaping Attention to News Information
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An algorithm audit of the Google Top Stories box is presented, indicating a considerable degree of source concentration, a slight exaggeration in the ideological skew of news in comparison to a baseline, and a quantification of how the presentation of items translates into traffic and attention for publishers.
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