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Recommending news in traditional media companies
Norwegian Univ Sci & Technol NTNU, Dept Comp Sci, Trondheim, Norway..
Norwegian Res Ctr Innovat NorwAI, Bergen, Norway..
Norwegian Univ Sci & Technol NTNU, Trondheim, Norway..
KTH.
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2021 (English)In: The AI Magazine, ISSN 0738-4602, Vol. 42, no 3, p. 55-69Article in journal (Refereed) Published
Abstract [en]

The adoption of recommender systems in online news personalization has made it possible to tailor the news stream to the individual interests of each reader. Previous research on commercial recommender systems has emphasized their use in large-scale media houses and technology companies, and real-world experiments indicate substantial improvements of click rates and user satisfaction. It is less understood how smaller media houses are coping with this new technology, how the technology affects their business models, their editorial processes, and their news production in general. Here we report on the experiences from numerous Scandinavian media houses that have experimented with various recommender strategies and streamlined their news production to provide personalized news experiences. In addition to influencing the content and style of news stories and the working environment of journalists, the news recommender systems have been part of a profound digital transformation of the whole media industry. Interestingly, many media houses have found it undesirable to automate the entire recommendation process and look for approaches that combine automatic recommendations with editorial choices.

Place, publisher, year, edition, pages
AMER ASSOC ARTIFICIAL INTELL , 2021. Vol. 42, no 3, p. 55-69
National Category
Media and Communication Studies Computer Sciences Building Technologies
Identifiers
URN: urn:nbn:se:kth:diva-307767DOI: 10.1609/aaai.12017ISI: 000744477000006OAI: oai:DiVA.org:kth-307767DiVA, id: diva2:1635817
Note

QC 20220208

Available from: 2022-02-08 Created: 2022-02-08 Last updated: 2025-02-11Bibliographically approved

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Stenbom, Agnes

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