论文标题
在家工作新规范吗？一项基于大型地理标签的Covid-19 Twitter数据集的观察性研究
Is Working From Home The New Norm? An Observational Study Based on a Large Geo-tagged COVID-19 Twitter Dataset
论文作者
论文摘要
当Covid-19的大流行席卷世界时，人们讨论了事实，表达了观点并在社交媒体上分享了情感。由于在不同地点对COVID-19的反应可能与当地案件，政府法规，医疗资源和社会经济因素有关，因此我们策划了一个大型地理标签的Twitter数据集，并按照位置进行了探索性分析。具体而言，我们在美国（50个州和华盛顿特区）收集了650,563个独特的地理标签推文，涵盖了2020年1月25日至2020年5月10日的日期范围。推文的地点使我们能够进行特定地区的研究，例如在推文量和情感上，有时是针对地方法规和报道的Covid-19案例。在此期间，许多人开始在家工作。每小时推文量之间的工作日和周末之间的差距激发了我们提出算法，以估算COVID-19危机期间的工作参与。本文还使用社交媒体独家工具（即#hashtags，@mentions）和潜在的dirichlet分配模型总结了我们数据集中推文的主题和主题。我们欢迎请求数据共享和对话以获取更多见解。 数据集链接：http：//covid19research.site/geo-tagged_twitter_datasets/
As the COVID-19 pandemic swept over the world, people discussed facts, expressed opinions, and shared sentiments on social media. Since the reaction to COVID-19 in different locations may be tied to local cases, government regulations, healthcare resources and socioeconomic factors, we curated a large geo-tagged Twitter dataset and performed exploratory analysis by location. Specifically, we collected 650,563 unique geo-tagged tweets across the United States (50 states and Washington, D.C.) covering the date range from January 25 to May 10, 2020. Tweet locations enabled us to conduct region-specific studies such as tweeting volumes and sentiment, sometimes in response to local regulations and reported COVID-19 cases. During this period, many people started working from home. The gap between workdays and weekends in hourly tweet volumes inspired us to propose algorithms to estimate work engagement during the COVID-19 crisis. This paper also summarizes themes and topics of tweets in our dataset using both social media exclusive tools (i.e., #hashtags, @mentions) and the latent Dirichlet allocation model. We welcome requests for data sharing and conversations for more insights. Dataset link: http://covid19research.site/geo-tagged_twitter_datasets/
