Local news has become increasingly important in the news industry due to its various benefits. It offers local audiences information that helps them participate in their communities and interests. It also serves as a reliable source of factual reporting that can prevent misinformation. Moreover, it can influence national audiences as some local stories may have wider implications for politics, environment or crime. Hence, detecting the exact geolocation and impact scope of local news is crucial for news recommendation systems. There are two fundamental things required in this process, (1) classify whether an article belongs to local news, and (2) identify the geolocation of the article and its scope of influence to recommend it to appropriate users. In this paper, we focus on the second step and propose (1) an efficient approach to determine the location and radius of local news articles, (2) a method to reconcile the user's location with the article's location, and (3) a metric to evaluate the quality of the local news feed. We demonstrate that our technique is scalable and effective in serving hyperlocal news to users worldwide.

翻译：本地新闻因诸多优势在新闻行业中日益重要。它向本地受众提供有助于参与社区生活、满足兴趣的信息，同时作为事实报道的可靠来源，可有效防止虚假信息传播。此外，某些本地故事可能对政治、环境或犯罪等领域产生更广泛的影响，从而影响全国受众。因此，精准识别本地新闻的地理位置及影响范围对新闻推荐系统至关重要。该过程包含两项基础任务：（1）判断文章是否属于本地新闻，（2）确定文章的地理位置及其影响范围，以便推荐给合适的用户。本文聚焦第二步，提出：（1）一种高效确定本地新闻文章位置与半径的方法，（2）一种协调用户位置与文章位置的策略，（3）一种评估本地新闻推送质量的指标。实验证明，我们的方法具有可扩展性，能够有效为全球用户提供超本地新闻服务。