CRII: III: Measuring the alignment between the interests of local communities, local news, and the national news media

由于公民兴趣将国家和地方社区主题结合在一起，它们与在线新闻来源的互动预计将反映这种关注的二重性。例如，在线新闻应该将关于当地学区的故事和关于国家利益的故事结合起来。在这个奖项中，研究人员将促进我们对地方和国家新闻报道如何满足当地社区的需求和利益的理解。这些发现可以提供更有效的沟通策略，并提高我们对影响社区的关键问题的了解。这项研究包括四个主要方面。首先，创建一个新的纵向地方新闻储存库，以补充研究人员过去与互联网档案馆合作开创的现有纵向国家新闻储存库。其次，该项目将研究新的自然语言处理(NLP)方法，以确定新闻覆盖或未覆盖的地理位置，以在快速变化的新闻版图中提供对新闻沙漠的动态衡量。第三，该项目将挖掘社区的兴趣和需求，通过社交媒体和搜索趋势的主题来表达。第四，该项目将探索当地社区利益与新闻主题之间的一致性。通过实现这些目标，这项研究将在建立纵向地方新闻数据集方面创造新的技术和最佳做法，这可能是不同学科的研究人员通过当地媒体研究美国的宝贵资源。此外，这一努力将开创新的NLP模式，以确定新闻报道所覆盖的社区，并绘制当地新闻沙漠的范围，以揭示被忽视和被边缘化的社区。此外，拟议的活动将量化社区利益与新闻故事之间的一致程度。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

As citizen interests combine national and local community topics, their interaction with online news sources is expected to reflect this duality of focus. For example, online news should combine stories about local school districts and ones about national interests. In this award, the researchers will advance our understanding of how local and national news reports address the needs and interests of local communities. The findings could inform more effective communication strategies and improve our knowledge of critical issues affecting communities.This research comprises four main thrusts. First, creating a novel longitudinal local news repository to complement an existing longitudinal national news repository the researchers pioneered in a past collaboration with the Internet Archive. Second, the project will research new natural language processing (NLP) approaches to identify the geographic locations covered or not covered by the news, to provide a dynamic measurement of news deserts in a rapidly changing news landscape. Third, the project will mine community interests and needs expressed by topics on social media and search trends. Fourth, the project will explore the alignment between the interests of local communities and news topics. By fulfilling these goals, this research would create new techniques and best practices in building longitudinal local news datasets, which could be a valuable resource for researchers from different disciplines to study the United Stated via local media. Additionally, this effort would pioneer novel NLP models for identifying communities covered by news reports, and map the extent of local news deserts to unveil neglected and marginalized communities. Moreover, the proposed activities will quantify the degree of alignment between community interests and news stories.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.