论文标题
美国州长和内阁高管中的Covid-19 Twitter叙述的动态主题建模
Dynamic topic modeling of the COVID-19 Twitter narrative among U.S. governors and cabinet executives
论文作者
论文摘要
联邦和州级决策的结合塑造了美国对Covid-19的反应。在本文中，我们通过将动态主题模型应用于美国州长和总统内阁成员相关推文，分析了有关该决策的叙述。我们使用网络霍克斯二项式主题模型来跟踪有关风险，测试和治疗的不断发展的子主题。我们还使用网络霍克斯进程推断出的Granger因果关系，在政府官员中构建了影响网络。
A combination of federal and state-level decision making has shaped the response to COVID-19 in the United States. In this paper we analyze the Twitter narratives around this decision making by applying a dynamic topic model to COVID-19 related tweets by U.S. Governors and Presidential cabinet members. We use a network Hawkes binomial topic model to track evolving sub-topics around risk, testing and treatment. We also construct influence networks amongst government officials using Granger causality inferred from the network Hawkes process.
