Adwita Arora¹, Krish Chopra¹, Divya Chaudhary², Ian Gorton² and Bijendra Kumar¹, ¹Netaji Subhas University of Technology, India, ²Northeastern University, USA

The COVID-19 pandemic has forced people to resort to social media to express their thoughts and opinions, which could be analysed further. In this paper, we aim to analyse the impact of the COVID-19 pandemic on social media users by Sentiment analysis of data collected from popular social media platforms, Twitter and Reddit. The textual data is preprocessed and is made fit for proper sentiment analysis using two unsupervised methods, VADER and TextBlob. Special care is taken to translate tweets or comments not in the English language to ensure their proper classification. We perform a comprehensive analysis of the emotions of the users specific to the COVID pandemic along with a time-based analysis of the trends, and a comparison of the performance of both the tools used. Geographical distribution of the sentiments is also done to see how they vary across regional boundaries.

Sentiment Analysis, Social Media Analysis, Natural Language Processing, COVID-19