Twitter Sentiment Analysis of COVID-19 In India: VADER Perspective

This paper aims to explore the sentiments of the Indian population towards COVID-specific events that occurred between 2020 and 2021, and investigate possible correlations. Using the COV19Tweets dataset from IEEE and the VADER sentiment analysis tool, the study finds that while some COVID-related events align with the sentiment score, others do not relate as expected. The paper presents a detailed discussion of the approach, dataset, tools, and findings, offering a visual representation of how COVID-19 unfolded in India. The research makes notable contributions, including highlighting the superior performance of VADER over TextBlob’s sentiment ratings in categorizing COVID-19-related tweets, demonstrating a significant association between the events and general sentiment during COVID-19, and providing a user-friendly web application to visualize and compare sentiment scores of COVID-19 events in India with a time-series feature. The paper concludes that this framework could be applied in crisis situations to understand them differently.