Controlled Personalization in Legacy Media Online Services: A Case Study in News Recommendation
This addresses the problem for legacy news organizations seeking to adopt personalization technologies while balancing editorial values, representing an incremental approach to existing methods.
The study tackled the challenge of implementing personalized news recommendations in legacy media by evaluating a controlled personalization strategy through an A/B test on a major Norwegian news website, finding that it increased click-through rates, reduced navigation effort, and improved content diversity and catalog coverage while reducing popularity bias.
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 paper, 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.