CCRI: Planning: RecommendNews: Community Research Infrastructure for Online Field Experiments

CCRI：规划：推荐新闻：在线现场实验的社区研究基础设施

• 批准号: 2016397
• 负责人: Joseph Konstan
• 金额: $ 10万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2023-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016397&HistoricalAwards=false
• 关键词: CCRI; Planning; RecommendNews; Community; Research

This planning grant will develop a shared vision and the partnerships required for an innovative research infrastructure that includes not only a computer system but also a community of users, for the development of new forms of recommender system applied to online news. There are three key broader impacts for this planning grant, and the subsequent infrastructure based on the plan. First, news recommendation has clear societal importance. Organizing the research community to support work on diversity, transparency, credibility, and effective news recommendation is a benefit not only for research, but for society. Second, the planned infrastructure has the potential to benefit not only the core research communities targeted, but also other research communities across the nation and around the world, including those in journalism and mass communication. Third, the planning process will engage a diverse set of researchers, including many from areas traditionally underserved, to extend the impact of this work as far as possible. The design, construction, and governance of this infrastructure has significant research challenges. In this case, the system is a news recommender application (plus the back-end to support it) and the users will be people who read news through the application. The infrastructure also includes experimental controls to allow researchers to run experiments by varying the recommendation algorithms and interfaces of the application and measuring results. Such infrastructure can reinvigorate research in recommender systems by enabling new applications, study designs, and success metrics. Central to this project is a series of outreach activities and planning meetings for the community. These range from a broad survey and a community forum for 100 researchers (held in conjunction with a conference) to smaller meetings of intended users and partners in implementation. These meetings will identify community needs and priorities, design both the infrastructure itself and the governance models needed to operate it, and develop models to ensure sustainability. This planning effort will engage a diverse subset of the research community in deep and thoughtful discussions about what research we are unable to carry out in academic settings today, what research we value, and what infrastructure we need to advance research in the field.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项计划拨款将为创新研究基础设施（不仅包括计算机系统，还包括用户社区）建立共同的愿景和伙伴关系，以开发适用于在线新闻的新形式的推荐系统。这项规划拨款以及基于该计划的后续基础设施有三个关键的更广泛的影响。首先，新闻推荐具有明显的社会重要性。组织研究团体来支持多样性、透明度、可信度和有效的新闻推荐工作，这不仅有利于研究，也有利于社会。其次，计划中的基础设施不仅有可能使核心研究社区受益，而且有可能使全国和世界各地的其他研究社区受益，包括新闻和大众传播领域的研究社区。第三，规划过程将吸引各种各样的研究人员，包括许多来自传统上服务不足的地区的研究人员，以尽可能扩大这项工作的影响。这种基础设施的设计、构建和治理具有重大的研究挑战。在本例中，系统是一个新闻推荐应用程序（加上支持它的后端），用户将是通过该应用程序阅读新闻的人。该基础设施还包括实验控制，允许研究人员通过改变推荐算法和应用程序的接口以及测量结果来运行实验。这样的基础设施可以通过启用新的应用程序、研究设计和成功度量来重振推荐系统中的研究。这个项目的核心是一系列的外展活动和社区规划会议。这些范围从广泛的调查和100名研究人员的社区论坛（与会议一起举行）到目标用户和执行伙伴的小型会议。这些会议将确定社区的需求和优先事项，设计基础设施本身和运营基础设施所需的治理模式，并开发确保可持续性的模式。这一规划工作将吸引研究界的不同子集进行深入和深思熟虑的讨论，讨论我们今天在学术环境中无法开展的研究，我们重视哪些研究，以及我们需要哪些基础设施来推进该领域的研究。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Towards an Experimental News User Community as Infrastructure for Recommendation Research

建立实验性新闻用户社区作为推荐研究的基础设施

• 发表时间: 2021
• 期刊: Proceedings of INRA'21: 9th International Workshop on News Recommendation and Analytics
• 作者: Konstan, Joseph A.;Burke, Robin;Malthouse, Edward C.
• 通讯作者: Malthouse, Edward C.