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Cited by 24Media Influence and PoliticsRecommender Systems and TechniquesMisinformation and Its Impacts

Modeling news recommender systems’ conditional effects on selective exposure: evidence from two online experiments

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Knudsen, Erik·2023·Journal of Communication
DOI 10.1093/joc/jqac047
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Abstract

Under which conditions do news recommender systems (NRSs) amplify or reduce selective exposure? I provide the Recommender Influenced Selective Exposure framework, which aims to enable researchers to model and study the conditional effects of NRSs on selective exposure. I empirically test this framework by studying user behavior on a news site where the choice environment is designed to systematically influence selective exposure. Through two preregistered online experiments that simulate different NRSs and unobtrusively log user behavior, I contribute empirical evidence that an NRS can increase or decrease the chance that selective exposure occurs, depending on what the NRS is designed to achieve. These insights have implications for ongoing scholarly debates on the democratic impact of NRSs.

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  • Algorithms on social media platforms can amplify selective exposure by recommending content similar to what users already prefer or agree with.

    “Algorithms on social media platforms can amplify this effect by recommending content similar to what users already prefer or agree with, reinforcing selective exposure through personalization [22].”

    From Auditing Political Exposure Bias: Algorithmic Amplification on Twitter/X During the 2024 U.S. Presidential Election (2025) · cites this paper as [22]

    The section on NRSs’ causal effects says recommenders can promote articles resembling those users previously chose and describes a possible feedback loop that could increase selective exposure. But the study focuses on online news sites; the Discussion says its framework may be relevant to social media platforms, not that it establishes the claimed effect there. Page numbers are not available in our copy. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Knudsen, E.
Affiliations
University of Bergen (NO)
Corresponding author
Knudsen, Erik
ORCID
Knudsen, Erik
Venue
Journal of Communication
Publisher
Oxford University Press (OUP)
Published
2022-12-23
Volume
73
Issue
2
Pages
138-149
ISSN
  • 0021-9916 (ISSN-L)
  • 1460-2466
DOI
10.1093/joc/jqac047
OpenAlex
W4312203558
Cited by
24
References
2
Citations by year
2026: 8 · 2025: 10 · 2024: 6
FWCI
5.76
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Communication (publishedVersion, cc-by)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
Funders
  • Research Council of Norway
  • MediaFutures: Research Centre for Responsible Media Technology and Innovation
Topics
  • Social Sciences › Sociology and Political Science › Media Influence and Politics
  • Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
Keywords
news recommender systems, selective exposure, algorithmic amplification, news consumption behavior, choice environment

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