Abstract
The declaration by the World Health Organization and government-initiated actions by different countries for the COVID-19 vaccine have led to the rapid evolution of sentiments on various social media platforms. Real-time data related to vaccination has grown the need to anticipate the changes in vaccine uptake. Using Twitter dataset, the study models different emotions and their associated word. The emotions are majorly classified into hesitancy and willingness for vaccination. The study categorizes the tweets into pre-launch, post-launch, and booster doses of the COVID-19 vaccine. Based on comparative analysis, most sentiments were related to hesitancy for vaccination during pre-launch. In post-launch, the majority of sentiments were oriented towards willingness for vaccination. However, during the booster dose, the sentiments were oriented toward happy, adequate, and free emotions. Over the time period, the willingness of the COVID-19 vaccine has improved. The practitioners and policymakers can obtain real-time sentiments based on this approach and strategize the long-term vaccination policy for COVID-19 and other vaccination programs.
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