###### Abstract  
Social media, such as Twitter, is a source of exchanging information and opinion on global issues such as COVID-19 pandemic. In this study, we work with a database of around 1.2 million tweets collected across five weeks of April-May 2021 to draw conclusions about public sentiments towards the vaccination outlook when vaccinations become widely available to the population during the COVID-19 pandemic. We deploy natural language processing and sentiment analysis techniques to reveal insights about COVID-19 vaccination awareness among the public. Our results show that people have positive sentiments towards taking COVID-19 vaccines instead of some adverse effects of some of the vaccines. We also analyze people's attitude towards the safety measures of COVID-19 after receiving the vaccines. Again, the positive sentiment is higher than that of negative in terms of maintaining safety measures against COVID-19 among the vaccinated population. We also project that around 62.44% and 48% of the US population will get at least one dose of vaccine and be fully vaccinated, respectively, by the end of July 2021 according to our forecast model. This study will help to understand public reaction and aid the policymakers to project the vaccination campaign as well as health and safety measures in the ongoing global health crisis. social network; public sentiment; COVID-19; vaccination; natural language processing; time series forecasting; Twitter data; sentiment analysis +
Footnote †: journal:  
By 1 June 2021, there has been 3.57 million confirmed deaths and 171.19 million confirmed COVID-19 cases [10]. The situation has improved since vaccination of COVID-19 started to scale up. As we gain more evidence of the positive impacts of vaccination on transmission, it will help to strengthen public trust [11]. Considering this, analyzing the public opinion or sentiment is very important for motivating people to be vaccinated against COVID-19. This paper aims at analyzing public sentiment on COVID-19 vaccination and the aftermath of vaccination regarding health safety measures. We scrape tweets based on different keywords filtering related to vaccines and health and safety issues after vaccination to help us understand public reaction and aid policymakers to project the vaccination campaign as well as health and safety measures. Analyzing the Twitter content empowers health experts, policymakers to learn about the public's reaction to vaccination during the COVID-19 pandemic. It also elucidates people's opinions on the health guidelines for the prevention of COVID-19 after getting vaccinated. Discoveries from this analysis related to health are useful as fundamental examinations for building more thorough models, which can be utilized to create proposals for the larger public and establish meaningful strategies and policies. The tweets in this study have caught discussions about vaccination and health guidelines during COVID-19 in numerous nations. Social media information permits scientists and researchers to have a global point of view, which is particularly shrewd during a worldwide pandemic. This study can be replicated by scraping tweets regularly until the COVID-19 pandemic comes to an end for understanding the overall public sentiment while the vaccination campaign is ongoing. In another part of the paper, we try to show the recent forecasting of the US population to have an understanding of the current vaccination scenario in the USA. We aim to have an overview on whether the vaccination campaign is proceeding properly and people are aware of the situation. We find that our forecast model also predicts a similar percentage of population as the US Government is targeting by a certain timeline. If the predicted percentage had been less, it would be an indicator to emphasize more on vaccination campaign. In addition, the health and government officials could plan accordingly beforehand to handle such scenario.