用全国代表性调查生成新闻推荐的公共价值标签
Civic Ground Truth in News Recommenders: A Method for Public Value Scoring
- 通过全国代表问卷收集公众对新闻价值的判断
- 构建可跨新闻语料通用的价值标签体系
- 适合关注媒体社会责任与推荐公平性的研究者
新闻推荐系统（NRS）研究持续探索如何将编辑目标与公共服务价值等规范性目标融入现有系统。此前工作借助专家意见或用户反馈量化这些价值，为更具公共意识的推荐系统奠定基础。本文在此基础上提出一种公民真实值方法，通过大规模、结构化的受众评估，在全国代表性调查的基础上生成可泛化至更广泛新闻语料的价值标签，并结合自动化元数据增强实现高效标注。
原文摘要 · Abstract (English)
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.
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