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Investigating the Use of Algorithmic News Recommendation in the Scandinavian Daily Press

Bibliographic Data

ID22009672
AuthorsLynge Asbjørn Møller (0000-0002-1632-2253, Aarhus University, corresponding author)
Year2021
Publication date2021-09-15
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAoIR Selected Papers of Internet Research (JOURNAL)
Journal identifiersISSN: 2162-3317 • E-ISSN: 2162-3317
PublisherUniversity of Illinois Libraries (PUBLISHER)
DOI10.5210/spir.v2021i0.11986
OpenAlexW3200839587
LanguageEN
References cited11

This paper investigates the Scandinavian daily press’ efforts in and perspectives on algorithmic news recommendation. News recommender systems provide news organisations with new opportunities to offer more relevant and personalised news experiences, but their increasing use has also raised several concerns about whether and how algorithms should undertake important editorial decisions. Current literature offers only limited empirical insight into the actual use of these technologies in journalism, and this paper is the first to map the use of news recommender systems in the Scandinavian media system. Drawing on interviews with all 19 national newspapers within the Scandinavian daily press, the findings reveal that 17 newspapers use news recommender systems and 14 of these use personalisation. Most newspapers expressed positive attitudes toward the technologies, highlighting increased relevance and better opportunities to drive subscriptions. The extent of the use of news recommendation at the specific news media organisations is still limited due to concerns about algorithms interfering with journalistic priorities and a reluctance to jeopardise the brand value of the front page. Some newspapers address these concerns by allowing for editorial control through subjectively estimated journalistic input, revealing that journalistic norms and ideals affect the design and implementation of algorithms in journalism

Advertising · Business · Front page · Journalism · Media studies · News media · News values · Newspaper · Personalization · Political science · Public relations · Recommender system · Sociology · World Wide Web · Computer Science · Law · Media Studies and Communication

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Citation velocityhistorical
Highly citedNo

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