Covid-19 also known as the Corona virus is a viral disease from the SARS-CoV-2 family of a virus, as of December 2019 the first case of this virus infection was identified in Wuhan, China, and this seemingly isolated case soon became a global pandemic, whose effect was felt globally which also had colossal effects on both health, economic and political affairs. As of the time of this research, about 4.5 million people have died of the Corona virus and over 215 million people have already been infected by it. This pandemic stood out not just for its scale but for how social media was a major contribution to its spread as well as to curbing it. The power of social media was used to spread misinformation as well as to spread awareness on the subject, with both having a massive impact on the people. In this paper we will be running a sentimental analysis on Twitter under the keyword “Covid-19 and Corona virus”, Twitter is a powerful social media tool that is known for its ability to keep trends in the form of tweets, we will be drawing correlations between the peaks of tweet with the peak of infection. We will also be analyzed to know the impact these tweets are having on the rate of infection and vice versa. We will also be analyzing what people are tweeting most about, what are the talking points, and comparing both real-time and past tweets with real-time infection and death rates using deep different learning methods to access what information can be derived from it.