论文标题
社交媒体上的采矿冠状病毒（COVID-19）帖子
Mining Coronavirus (COVID-19) Posts in Social Media
论文作者
论文摘要
世界卫生组织（WHO）将新颖的冠状病毒（Covid-19）描述为2020年3月11日的全球大流行。在此之前和1月下旬，更具体地说，在1月27日更具体地说，中国的大多数感染案例仍在中国报道，我们开始使用Twitter Search搜索API爬行社交媒体用户。我们的目标是利用机器学习和语言工具，以更好地了解中国爆发的影响。与我们最初对当地爆发监测的期望不同，Covid-19迅速遍布全球。在这篇简短的文章中，我们报告了我们的研究的初步结果，这些结果是使用最先进的机器学习模型自动从社交媒体用户帖子中从社交媒体用户发布中的阳性报告。
World Health Organization (WHO) characterized the novel coronavirus (COVID-19) as a global pandemic on March 11th, 2020. Before this and in late January, more specifically on January 27th, while the majority of the infection cases were still reported in China and a few cruise ships, we began crawling social media user postings using the Twitter search API. Our goal was to leverage machine learning and linguistic tools to better understand the impact of the outbreak in China. Unlike our initial expectation to monitor a local outbreak, COVID-19 rapidly spread across the globe. In this short article we report the preliminary results of our study on automatically detecting the positive reports of COVID-19 from social media user postings using state-of-the-art machine learning models.
