Government Health Communication During the COVID-19 Pandemic: A BERT Topic Modeling Approach

Abstract

Different levels of government agencies have exerted great effort to communicate with the public during the Covid-19 pandemic on multiple social media platforms. This study uses BERT topic modeling, an artificial intelligence model, to extract topics from various public health agencies of cities, states and the federal government on Twitter and Facebook for the years 2020 and 2021. We contrast and compare major topics addressed by these agencies related to Covid-19 and the pandemic across the two major social media platforms. The findings show how we can employ BERT topic modeling to extract social media topics during a health emergency and evaluate the extent to which topics covered by these agencies address the major social and health concerns of the pandemic.