Sentiment Prediction on COVID-19 Vaccination Reviews

COVID-19 pandemic has afflicted millions of people worldwide, resulting in three million deaths. Many medical experts and authorities have been striving to combat this pandemic using vaccines. Nowadays, various types of vaccines are available in different countries. Many people around the world have already been vaccinated and many are still receiving. Sharing opinions about vaccines has become a natural phenomenon for the last one plus years where social media platforms play a major role. In this line, people who received the vaccine expressed their sentiments towards the COVID-19 vaccination on Twitter on a large scale. In this study, sentiment predictive models such as Support Vector Machine (SVM), Logistic Regression and Multinomial Naive Bayes were developed with the feature extraction methods like Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TFIDF) to predict according to the analysis, the SVM model outperformed with the accuracy of 87.89%(TFIDF) and 87.40% (BoW).