arXiv:2510.09136cs.IRcs.AI2025-10被引 1

传统媒体用有限个性化提升点击率与内容多样性

Controlled Personalization in Legacy Media Online Services: A Case Study in News Recommendation

  • 结合编辑精选与算法推荐,实现可控个性化
  • 个性化用户点击率更高,导航更省力,内容覆盖更广
  • 适合重视内容质量与公信力的新闻机构参考

个性化新闻推荐已成为大型新闻聚合平台的标准功能,通过自动化内容选择优化用户参与度。相比之下,传统新闻媒体在个性化方面较为谨慎,力求在技术创新与核心编辑价值间取得平衡。因此,传统媒体的在线平台通常将编辑策划内容与算法推荐文章相结合——我们称之为‘可控个性化’。本文通过对一家主要挪威传统新闻机构网站开展A/B测试,评估该策略的效果。结果表明,即使采用较温和的个性化策略,也能带来显著收益:接受个性化内容的用户点击率更高、导航负担更低,表明其更易发现相关资讯。此外,分析显示,可控个性化提升了内容多样性与全库覆盖度,并降低热门内容偏倚。总体而言,该策略能有效兼顾用户需求与编辑目标,为传统媒体在坚守新闻价值的前提下采纳个性化技术提供可行路径。

原文摘要 · Abstract (English)

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.

新闻推荐可控个性化传统媒体

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