Dynamic topic modeling of twitter data during the COVID-19 pandemic

• DOI: 10.1371/journal.pone.0268669
• Publication Date: 2022-05-27T17:36:13Z
• Authors: Alexander Bogdano...; ChengHe Guan
• Keywords: Pandemic; 2019-20 coronavirus outbreak

In an effort to gauge the global pandemic's impact on social thoughts and behavior, it is important answer following questions: (1) What kinds of topics are individuals groups vocalizing in relation pandemic? (2) Are there any noticeable topic trends if so how do these change over time response major events? this paper, through advanced Sequential Latent Dirichlet Allocation model, we identified twelve most popular present a Twitter dataset collected period spanning April 3rd 13th, 2020 United States discussed their growth changes time. These were both robust, that they covered specific domains, not simply events, dynamic, able rising our dataset. They spanned politics, healthcare, community, economy, experienced macro-level time, while also exhibiting micro-level composition. Our approach differentiated itself scale scope study emerging concerning COVID-19 at few works have been achieve. We contributed cross-sectional field urban studies big data. Whereas optimistic towards future, understand unprecedented will lasting impacts society large, impacting only economy or geo-politics, but human behavior psychology. Therefore, more ways than one, research just beginning scratch surface what be concerted into studying history repercussions COVID-19.