Public Perception of COVID-19 Vaccines through Analysis of Twitter Content and Users

Twitter is a robust medium to understand wide-scale, organic public perception about the COVID-19 vaccine. In this cross-sectional observational study, we evaluated 2.4 million English tweets from nearly 1 million user accounts matching keywords ((‘covid*’ OR ‘coronavirus’) AND ‘vaccine’) during vaccine development from Feb 1stthrough Dec 11th, 2020. We applied topic modeling, sentiment and emotion analysis, and demographic inference of users on the COVID-19 vaccine related tweets to provide insight into the evolution of public attitudes. Individuals generated 87.9% (n=834,224) of tweets. Of individuals, men (n=560,824) outnumbered women (n=273,400) by 2:1 and 39.5% (n=329,776) of individuals were ≥ 40 years old. Daily mean sentiment fluctuated congruent with news events, but overall trended positively. Trust, anticipation, and fear were the three most predominant emotions; while fear was the most predominant emotion early in the study period, trust outpaced fear from April 2020 onward. Fear was more prevalent in tweets by individuals (26.3% vs. organizations 19.4%; p