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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.22865 |
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| _version_ | 1866911234175008768 |
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| author | Meese, James Herbertson, Kyle |
| author_facet | Meese, James Herbertson, Kyle |
| contents | Research in news recommendation systems (NRS) continues to explore the best ways to integrate normative goals such as editorial objectives and public service values into existing systems. Prior efforts have incorporated expert input or audience feedback to quantify these values, laying the groundwork for more civic-minded recommender systems. This paper contributes to that trajectory, introducing a method for embedding civic values into NRS through large-scale, structured audience evaluations. The proposed civic ground truth approach aims to generate value-based labels through a nationally representative survey that are generalisable across a wider news corpus, using automated metadata enrichment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_22865 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Civic Ground Truth in News Recommenders: A Method for Public Value Scoring Meese, James Herbertson, Kyle Information Retrieval Research in news recommendation systems (NRS) continues to explore the best ways to integrate normative goals such as editorial objectives and public service values into existing systems. Prior efforts have incorporated expert input or audience feedback to quantify these values, laying the groundwork for more civic-minded recommender systems. This paper contributes to that trajectory, introducing a method for embedding civic values into NRS through large-scale, structured audience evaluations. The proposed civic ground truth approach aims to generate value-based labels through a nationally representative survey that are generalisable across a wider news corpus, using automated metadata enrichment. |
| title | Civic Ground Truth in News Recommenders: A Method for Public Value Scoring |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2510.22865 |