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

由于公民的利益联合收割机结合了国家和地方社区的主题，他们与在线新闻来源的互动预计将反映这种双重重点。例如，网络新闻应该将有关当地学区的联合收割机报道和有关国家利益的报道结合起来。在这个奖项中，研究人员将推进我们对地方和国家新闻报道如何满足当地社区需求和利益的理解。研究结果可以为更有效的传播战略提供信息，并提高我们对影响社区的关键问题的认识。首先，创建一个新的纵向本地新闻库，以补充现有的纵向国家新闻库，研究人员在过去与互联网档案馆的合作中开创了这一领域。其次，该项目将研究新的自然语言处理（NLP）方法，以识别新闻覆盖或未覆盖的地理位置，在快速变化的新闻环境中提供新闻沙漠的动态测量。第三，该项目将挖掘社交媒体和搜索趋势主题所表达的社区兴趣和需求。第四，该项目将探讨当地社区的利益与新闻主题之间的一致性。通过实现这些目标，这项研究将创造新的技术和最佳实践，在建设纵向本地新闻数据集，这可能是一个宝贵的资源，为研究人员从不同学科研究美国通过当地媒体。此外，这一努力将开创新的NLP模型，用于识别新闻报道所覆盖的社区，并绘制当地新闻沙漠的范围，以揭示被忽视和边缘化的社区。此外，拟议的活动将量化社区利益和新闻报道之间的一致程度。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.