NELA-Local

NELA-Local数据集是由田纳西大学诺克斯维尔分校信息科学学院等机构创建，包含超过140万篇来自美国313个地方新闻网站的在线新闻文章，覆盖了20个月的时间跨度。该数据集不仅包含新闻内容，还关联了县级的元数据，如人口统计、政治倾向和社区韧性评估，以帮助研究者分析地方新闻对社区的影响。数据集的创建过程涉及使用RSS feeds收集文章URL，并通过网络爬虫获取全文。NELA-Local数据集主要用于研究地方新闻的覆盖范围、内容多样性及其对社区决策的影响，特别是在重大事件如2020年美国总统选举和COVID-19疫情期间的作用。

The NELA-Local dataset was developed by the School of Information Science at the University of Tennessee, Knoxville, and other affiliated institutions. It comprises over 1.4 million online news articles from 313 local news websites across the United States, spanning a 20-month period. In addition to the core news content, the dataset also includes county-level metadata such as demographic statistics, political leanings, and community resilience assessments, to assist researchers in analyzing the impact of local news on local communities. The dataset was constructed by collecting article URLs via RSS feeds and retrieving full news texts through web crawling. The NELA-Local dataset is primarily intended for research on the coverage scope, content diversity of local news, and their impacts on community decision-making, particularly their roles during major events including the 2020 U.S. presidential election and the COVID-19 pandemic.