Sentiment Analysis to Compare Tweets About Online Education During and After COVID-19

Abstract

COVID-19 affected the world drastically in various terms. It has been transmitted throughout the globe with infectious air whose impacts were not assumed or expected. The education system faced many challenges due to it and suffered a lot but the rise of online education gave people, institutions, and schools another hope to continue their learning by being connected and conducting classes over the internet. In this paper, we seek to study and compare the responses of people from the community during and after COVID-19 about online education learning by analysing the tweets from the social media platform called Twitter. For classification, Naive Bayes algorithm has been used and an accuracy of 85.4% has been achieved. By this study, we concluded that during COVID-19 most of the people had negative opinions about online education, but the after COVID-19 datasets show a certain rise in the figures of neutral and positive tweets and a decrease in the number of negative tweets.