• Banshri Modhiya
• Poonam Faldu
• Niharika Solanki

Microblogging today has become a very popular communication tool among Internet users. Millions of users share opinions on different aspects of life every day. Therefore microblogging web-sites are rich sources of data for opinion mining and sentiment analysis. Because microblogging has appeared relatively recently, there are a few research works that were devoted to this topic. In our paper, we focus on using Twitter, the most popular microblogging platform, our purpose of this paper is to introduce a new strategy to identify how the peoples are responding to the government’s decision of lockdown. Crowded regions with actively moving people (called at-risk regions) are susceptible to spreading the disease, especially if they contain asymptomatic infected people together with healthy people so the government took the very important decision of Lockdown. In this paper we have proposed identifies the sentiments of the tweets with the relevant #tags of COVID. The Tweets was collected by Twitter’s API then the tweets was stored in the database and then the frequency of words in the tweets was analyzed by IBM’s NLP and will return the sentiment of the tweet, from that extracted sentiments we’ll get to know how the citizens take the government’s decision, it was also allow us to identify whether to extend lockdown or not.

COVID-19, Lockdown, Sentiment

"Sentiment Analysis of COVID-19 Tweets Visualization Dashboard", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.d796-d803, April-2022, Available :http://www.jetir.org/papers/JETIR2204393.pdf

"Sentiment Analysis of COVID-19 Tweets Visualization Dashboard", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppd796-d803, April-2022, Available at : http://www.jetir.org/papers/JETIR2204393.pdf