Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets (Preprint)

Abstract

BACKGROUND During the pandemic of COVID-19, United States public health authorities and county, state, and federal governments recommended or ordered certain preventative practices, such as wearing masks, to reduce the spread of the disease. However, individuals had divergent reactions to these preventive practices. OBJECTIVE The purpose of the study was to understand the variations of public sentiment towards COVID-19 and the recommended or ordered preventive practices from the temporal and spatial perspectives, and how the variations in public sentiment are related to geographical and socioeconomic factors. METHODS The authors leveraged machine learning methods to investigate public sentiment polarity in COVID-19-related Tweets, from January 21, 2020, to June 12, 2020. The study measured the temporal variations and spatial disparities in public sentiment towards both general COVID-19 topics and preventive practices in the United States. RESULTS In the temporal analysis, we found a four-stage pattern from high negative sentiment in the initial stage, to decreasing and low negative sentiment in the second and third stage, to the rebound and increase of negative sentiment in the last stage. We also identified that public sentiment to preventive practices was significantly different in urban and rural areas, while poverty rate and unemployment rate were positively associated with negative sentiment to COVID-19 issues. CONCLUSIONS The differences between public sentiment towards COVID-19 and the preventive practices imply that actions need to be taken to manage the initial and the rebound stage in future pandemics. The urban/rural differences should be considered in terms of the communication strategies and decision-makings during a pandemic. This research also presents a framework to investigate time-sensitive public sentiment at the county and state level, which could guide local and state governments, and regional communities in making decisions and developing policies in crises. CLINICALTRIAL