Before revision:  COVID-19 vaccination drives across the globe are accompanied by a wide variety of expressed opinions , often colored by emotions . We extracted a corpus of Twitter posts related to COVID-19 vaccination and created two classes of lexical categories- Emotions and Influencing factors. Using unsupervised word embeddings, we tracked the longitudinal change in the latent space of the lexical categories in five countries with strong vaccine roll-out programs, i.e. India, USA , Brazil, UK , and Australia.
After revision:  COVID-19 vaccination drives across the globe are accompanied by a wide variety of expressed opinions , often colored by emotions , which change along with rising cases, approval of vaccines, and multiple factors discussed online. This study aims at analyzing the temporal evolution of different Emotion categories: Hesitation, Rage, Sorrow, Anticipation, Faith, and Contentment with Influencing Factors: Vaccine Rollout, Misinformation, Health Effects, and Inequities as lexical categories created from Tweets belonging to five countries with strong vaccine roll-out programs, i.e. India, USA , Brazil, UK , and Australia.