Use of two topic modeling methods to investigate covid vaccine hesitancy

Abstract

COVID vaccine hesitancy in the face of a pandemic is a concern for public health researchers and policy makers who aim to achieve herd immunity. We investigated the COVID vaccine hesitancy by analyzing Twitter posts (tweets) using two topic modeling methods: Latent Dirichlet Allocation (LDA) and Top2Vec. Of the two methods, Top2Vec was able to reveal topics which directly discussed Vaccine Hesitancy and thus offered more utility for this research topic. Common reasons for vaccine hesitancy found in the dataset included concerns about recent (at the time of tweet collection) news regarding side effects associated with the COVID vaccines, and a mixture of scientific and government skepticism related to vaccine development and distribution.