• ARCHANAKUMAREE DINESHBHAI BHUSARA
• Prachi Pancholi

We are living in the information era, where data is growing rapidly. During critical events, people share their opinion on social media. Nowadays, the world is confronting an infectious disease called COVID-19 or Coronavirus. As social distancing and lockdown are considered the most considerate way to stay away from disease. Therefore, the usage of social media is increased, and a survey shows that during lockdown 3.3 million tweets a day reported on COVID-19. People are using social media for help and to express their opinion on the global pandemic. There are many social networking sites people use to share their opinion, but Twitter has emerged as one of the most popular social media among all other social media. We have done sentiment analysis on big data created by this social media. In this study, we used Twitter to study sentiment analysis. Our dataset contains 1,88,880 tweets on COVID-19. On this dataset, we used different feature extraction methods with the Naïve Bayes machine learning approach and get 84.63% accuracy on big data.

Sentiment Analysis, Opinion Mining, social media, COVID-19, Machine Learning

"Social Media Sentiment Analysis on COVID-19", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 11, page no.c489-c495, November-2021, Available :http://www.jetir.org/papers/JETIR2111267.pdf

"Social Media Sentiment Analysis on COVID-19", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 11, page no. ppc489-c495, November-2021, Available at : http://www.jetir.org/papers/JETIR2111267.pdf