  Social media plays a pivotal role in disseminating news globally and acts as
a platform for people to express their opinions on various topics. A wide
variety of views accompanies COVID-19 vaccination drives across the globe,
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 vital vaccine roll-out
programs, namely, India, United States of America, Brazil, United Kingdom, and
Australia. We extracted a corpus of nearly 1.8 million Twitter posts related to
COVID-19 vaccination. Using cosine distance from selected seed words, we
expanded the vocabulary of each category and tracked the longitudinal change in
their strength from June 2020 to April 2021. We used community detection
algorithms to find modules in positive correlation networks. Our findings
suggest that tweets expressing hesitancy towards vaccines contain the highest
mentions of health-related effects in all countries. Our results indicated that
the patterns of hesitancy were variable across geographies and can help us
learn targeted interventions. We also observed a significant change in the
linear trends of categories like hesitation and contentment before and after
approval of vaccines. Negative emotions like rage and sorrow gained the highest
importance in the alluvial diagram. They formed a significant module with all
the influencing factors in April 2021, when India observed the second wave of
COVID-19 cases. The relationship between Emotions and Influencing Factors was
found to be variable across the countries.
