Social Media Study of Public Opinions on Potential COVID-19 Vaccines: Informing Dissent, Disparities, and Dissemination
Hanjia Lyu, Junda Wang, Wei Wu, Viet Duong, Xiyang Zhang, Timothy D., Dye, Jiebo Luo

TL;DR
This study analyzes over six million tweets to understand public opinions on COVID-19 vaccines, revealing demographic and regional disparities, and informing vaccine policy strategies.
Contribution
It introduces a large-scale social media analysis framework to classify and analyze public vaccine opinions, linking them to socio-demographic factors and pandemic experiences.
Findings
Lower pro-vaccine sentiment in Southeast US
Socioeconomic disadvantage correlates with polarized opinions
Personal pandemic experience influences vaccine attitudes
Abstract
The current development of vaccines for SARS-CoV-2 is unprecedented. Little is known, however, about the nuanced public opinions on the vaccines on social media. We adopt a human-guided machine learning framework using more than six million tweets from almost two million unique Twitter users to capture public opinions on the potential vaccines for SARS-CoV-2, classifying them into three groups: pro-vaccine, vaccine-hesitant, and anti-vaccine. We aggregate opinions at the state and country levels, and find that the major changes in the percentages of different opinion groups roughly correspond to the major pandemic-related events. Interestingly, the percentage of the pro-vaccine group is lower in the Southeast part of the United States. Using multinomial logistic regression, we compare demographics, social capital, income, religious status, political affiliations, geo-locations,…
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Taxonomy
TopicsVaccine Coverage and Hesitancy · Misinformation and Its Impacts · Hate Speech and Cyberbullying Detection
