Overwhelmed by Fear: Emotion Analysis of COVID-19 Vaccination Tweets

Abstract

COVID-19, particularly vaccines, have caused an ‘infodemic’ online; a rapid and vast spread of unreliable information. While vaccines can minimize the detrimental effects of COVID-19, misinformation, fearmongering, and ‘anti-vax’ movements have fostered opposition which is especially prevalent on Twitter. Understanding public emotions related to vaccines is an important, yet inconsistent, area of research. To resolve some of the inconsistencies in the field, we develop and apply two integrated emotion detection models to a longitudinal sample of COVID-19 vaccine related tweets (n = 823,748). Contrary to prior research, which concluded that positive emotions are the most dominant emotion (e.g., trust and happiness), the balanced emotion model (consisting of eight emotions) shows that fear (41 %) is the most dominant emotion. The extended emotion model (consisting of sixteen emotions) shows various negative emotions such as panic (27%), fear (22%), and shame (37%) as the dominant emotions in the tweet hashtag groups such as COVID-19, Vaccine, and Anti-vaxxers.