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Main Authors: Holzleitner, Marlene, Leitner, Stephan, Jorgensen, Hanna Lind, Schmitz, Christoph, Welander, Jacob, Jannach, Dietmar
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.09136
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author Holzleitner, Marlene
Leitner, Stephan
Jorgensen, Hanna Lind
Schmitz, Christoph
Welander, Jacob
Jannach, Dietmar
author_facet Holzleitner, Marlene
Leitner, Stephan
Jorgensen, Hanna Lind
Schmitz, Christoph
Welander, Jacob
Jannach, Dietmar
contents Personalized news recommendations have become a standard feature of large news aggregation services, optimizing user engagement through automated content selection. In contrast, legacy news media often approach personalization cautiously, striving to balance technological innovation with core editorial values. As a result, online platforms of traditional news outlets typically combine editorially curated content with algorithmically selected articles - a strategy we term controlled personalization. In this industry article, we evaluate the effectiveness of controlled personalization through an A/B test conducted on the website of a major Norwegian legacy news organization. Our findings indicate that even a modest level of personalization yields substantial benefits. Specifically, we observe that users exposed to personalized content demonstrate higher click-through-rates and reduced navigation effort, suggesting improved discovery of relevant content. Moreover, our analysis reveals that controlled personalization contributes to greater content diversity and catalog coverage and in addition reduces popularity bias. Overall, our results suggest that controlled personalization can successfully align user needs with editorial goals, offering a viable path for legacy media to adopt personalization technologies while upholding journalistic values.
format Preprint
id arxiv_https___arxiv_org_abs_2510_09136
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Controlled Personalization in Legacy Media Online Services: A Case Study in News Recommendation
Holzleitner, Marlene
Leitner, Stephan
Jorgensen, Hanna Lind
Schmitz, Christoph
Welander, Jacob
Jannach, Dietmar
Information Retrieval
Artificial Intelligence
Personalized news recommendations have become a standard feature of large news aggregation services, optimizing user engagement through automated content selection. In contrast, legacy news media often approach personalization cautiously, striving to balance technological innovation with core editorial values. As a result, online platforms of traditional news outlets typically combine editorially curated content with algorithmically selected articles - a strategy we term controlled personalization. In this industry article, we evaluate the effectiveness of controlled personalization through an A/B test conducted on the website of a major Norwegian legacy news organization. Our findings indicate that even a modest level of personalization yields substantial benefits. Specifically, we observe that users exposed to personalized content demonstrate higher click-through-rates and reduced navigation effort, suggesting improved discovery of relevant content. Moreover, our analysis reveals that controlled personalization contributes to greater content diversity and catalog coverage and in addition reduces popularity bias. Overall, our results suggest that controlled personalization can successfully align user needs with editorial goals, offering a viable path for legacy media to adopt personalization technologies while upholding journalistic values.
title Controlled Personalization in Legacy Media Online Services: A Case Study in News Recommendation
topic Information Retrieval
Artificial Intelligence
url https://arxiv.org/abs/2510.09136