Burst of the Filter Bubble? Effects of personalization on the diversity of Google News

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 perso...

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Bibliographic Details
Published inDigital journalism Vol. 6; no. 3; pp. 330 - 343
Main Authors Haim, Mario, Graefe, Andreas, Brosius, Hans-Bernd
Format Journal Article
LanguageEnglish
Published Routledge 16.03.2018
Subjects
diversity
experiment
filter bubble
online news
personalization
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Summary: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, however, find a general bias in that Google News over-represents certain news outlets and under-represents other, highly frequented, news outlets. The results add to a growing body of evidence, which suggests that concerns about algorithmic filter bubbles in the context of online news might be exaggerated.
ISSN:2167-0811
2167-082X
DOI:10.1080/21670811.2017.1338145