In Social network analysis and mining
Social media have a significant impact on opinion building in public. Vaccination in India started in January 2021. We have seen many opinions towards vaccination of the people, as vaccination is one of the most crucial steps toward the fight against COVID-19. In this paper, we have compared the public's sentiments towards COVID vaccination in India before the second wave and after the second wave. We worked by extracting tweets regarding vaccination in India, building our datasets. We extracted 5977 tweets before the second wave and 42,936 tweets after the second wave. We annotated the collected tweets into four categories, namely Provaccine, Antivaccine, Hesitant and Cognizant. We built a baseline model for sentiment analysis and have used multiple classification techniques among which Random Forest using the TF-IDF vectorization technique gave the best accuracy of 69% using max-features and n-estimators as parameters.
Mishra Siddhi, Verma Abhigya, Meena Kavita, Kaushal Rishabh
Covid-19 vaccincation, Machine learning, Sentiment classification