What News Recommendation Research Did (But Mostly Didn't) Teach Us About Building A News Recommender
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866909789996449792 |
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| author | Higley, Karl Burke, Robin Ekstrand, Michael D. Knijnenburg, Bart P. |
| author_facet | Higley, Karl Burke, Robin Ekstrand, Michael D. Knijnenburg, Bart P. |
| contents | One of the goals of recommender systems research is to provide insights and methods that can be used by practitioners to build real-world systems that deliver high-quality recommendations to actual people grounded in their genuine interests and needs. We report on our experience trying to apply the news recommendation literature to build POPROX, a live platform for news recommendation research, and reflect on the extent to which the current state of research supports system-building efforts. Our experience highlights several unexpected challenges encountered in building personalization features that are commonly found in products from news aggregators and publishers, and shows how those difficulties are connected to surprising gaps in the literature. Finally, we offer a set of lessons learned from building a live system with a persistent user base and highlight opportunities to make future news recommendation research more applicable and impactful in practice. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_12361 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | What News Recommendation Research Did (But Mostly Didn't) Teach Us About Building A News Recommender Higley, Karl Burke, Robin Ekstrand, Michael D. Knijnenburg, Bart P. Information Retrieval Computers and Society Human-Computer Interaction One of the goals of recommender systems research is to provide insights and methods that can be used by practitioners to build real-world systems that deliver high-quality recommendations to actual people grounded in their genuine interests and needs. We report on our experience trying to apply the news recommendation literature to build POPROX, a live platform for news recommendation research, and reflect on the extent to which the current state of research supports system-building efforts. Our experience highlights several unexpected challenges encountered in building personalization features that are commonly found in products from news aggregators and publishers, and shows how those difficulties are connected to surprising gaps in the literature. Finally, we offer a set of lessons learned from building a live system with a persistent user base and highlight opportunities to make future news recommendation research more applicable and impactful in practice. |
| title | What News Recommendation Research Did (But Mostly Didn't) Teach Us About Building A News Recommender |
| topic | Information Retrieval Computers and Society Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.12361 |