Twitter Sentiment Analysis on Oxygen Supply During Covid 19 Outbreak

Abstract

AbstractThe COVID-19 emerged as a pandemic and affected many nations. World Health Organization [WHO] declared it as a worldwide pandemic alert on March 11, 2020, people had to stay indoors with lockdowns imposed, turning all daily activities to a halt. The lockdown was lifted in phase by manner from June 2020 as the cases were in control. A rise in pandemic was observed in many countries again in 2021, it was termed as the second wave of COVID-19. In India daily cases reached the mark of 4 lakhs in April 2021. This resulted in increased demand for oxygen supplies and other medical equipment’s to tackle the situation. With this, social media or the microblogging platforms like Twitter became a popular means of expressing emotions, making request for help and a daily information channel. The present study analyses the Twitter data extracted using Twitter API. It analyses and classifies people's sentiments related to the supply of oxygen during the second wave of the pandemic in India. The paper analyses the sentiment of the tweets for Indian users from June 20th, 2021, to June 26th, 2021, using Natural language processing (NLP) and Machine Learning (ML) techniques. KeywordsNLPSentiment analysisCOVID-19TwitterMachine learning