• Kirti Bala Bahekar
• Dr.Pratima Gautam
• Dr.Shailja Sharma

The world is suffering from a very destructive pandemic caused by a novel coronavirus named COVID19. Countries imposed lockdowns, various guidelines, and measures to prevent the spread of COVID19 among the citizens. Due to lockdown and strict guidelines for the public, a large number of people took the support of Social Media to express their opinions, thoughts, suffering’s and emotions. Twitter is a microblogging site, a platform for the public to write views in text format. Several researchers conducted studies on public sentiments during the pandemic period. This paper presents a review of some of the studies conducted, on community opinions during the pandemic, based on tweets. Further, we analyzed various researches on the prediction of tweets using a variety of machine learning algorithms. Moreover, the analysis also focuses on datasets and performance analysis measures are recognized. The research gap is also identified where more upcoming researches can concentrate.

COVID19, Machine Learning, Sentiment analysis, Performance analysis

"Literature Review on Sentiment Analysis and Opinion Classifications on the impact of COVID19 Outbreak", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 1, page no.a94-a99, January-2022, Available :http://www.jetir.org/papers/JETIR2201012.pdf

"Literature Review on Sentiment Analysis and Opinion Classifications on the impact of COVID19 Outbreak", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 1, page no. ppa94-a99, January-2022, Available at : http://www.jetir.org/papers/JETIR2201012.pdf