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Opportunity structures for user acceptance of news recommender systems (NRS): A multi-country survey study of relationships between individual-level factors and evaluations of NRS

Strikovic, Edina; Blassnig, Sina; Mitova, Eliza; Urman, Aleksandra; Esser, Frank; de Vreese, Claes (2024). Opportunity structures for user acceptance of news recommender systems (NRS): A multi-country survey study of relationships between individual-level factors and evaluations of NRS. New Media & Society:Epub ahead of print.

Abstract

Digitalization of the media is often discussed in terms of effects on the user. What is often overlooked are the motivations from users, on the individual level, for the acceptance of new technologies. This study explores what individual-level factors make up favorable opportunity structures for the implementation of news recommender systems (NRS). We conduct a cross-sectional survey ( n = 5073) in five countries (The Netherlands, Switzerland, Poland, the United Kingdom, and the United States) to analyze the correlations between users’ individual-level factors and their evaluations of NRS in terms of benefits and concerns. Our findings demonstrate universally critical evaluations of NRS and less-than-ideal conditions for the acceptance of NRS. We also show that while there are patterns of country differences, the perceived concerns of NRS are stronger overall and largely universal. Implications of these findings suggest a slow and intentional development and implementation of NRS rather than keeping pace with the fast development of technology.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
06 Faculty of Arts > Department of Communication and Media Research
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Social Sciences & Humanities > Communication
Social Sciences & Humanities > Sociology and Political Science
Uncontrolled Keywords:Algorithms, digital journalism, new media technologies, news recommender systems, user attitudes
Language:English
Date:26 July 2024
Deposited On:31 Oct 2024 15:27
Last Modified:28 Feb 2025 02:38
Publisher:Sage Publications
ISSN:1461-4448
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1177/14614448241263765
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  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

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