An analysis of vaccine-related sentiments from development to deployment
  of COVID-19 vaccines
Rohitash Chandra Jayesh Sonawane Janhavi Lande Cathy Yu
Anti-vaccine sentiments have been well-known and reported throughout the
history of viral outbreaks and vaccination programmes. The COVID-19 pandemic
had fear and uncertainty about vaccines which has been well expressed on social
media platforms such as Twitter. We analyse Twitter sentiments from the
beginning of the COVID-19 pandemic and study the public behaviour during the
planning, development and deployment of vaccines expressed in tweets worldwide
using a sentiment analysis framework via deep learning models. In this way, we
provide visualisation and analysis of anti-vaccine sentiments over the course
of the COVID-19 pandemic. Our results show a link between the number of tweets,
the number of cases, and the change in sentiment polarity scores during major
waves of COVID-19 cases. We also found that the first half of the pandemic had
drastic changes in the sentiment polarity scores that later stabilised which
implies that the vaccine rollout had an impact on the nature of discussions on
social media.