Sentiment Analysis of Twitter Tweets for COVID- 19 Pfizer Vaccines

Coronavirus pandemic, also referred to as COVID-19, broke out in 2019 and caused extensive illnesses. Many experts in the medical field are of the opinion that the epidemic first appeared in Wuhan, China, before it spread to other areas of the world. Washing one’s hands, covering one’s face, and socially isolating oneself from others are only some of the preventative methods that decision-makers have advocated. Early in 2021, a number of nations, notably the United States, started giving their citizens the COVID-19 vaccination. Since the World Health organization proclaimed that COVID-19 was causing a pandemic, there has been a concerted effort on a worldwide scale to create vaccinations against the virus. Because people often use social media, and Twitter in particular, to share their knowledge and attitudes on global topics such as COVID-19-vaccination, Twitter is an excellent tool for researching public perspectives. This research study performs a sentiment analysis of Pfizer vaccines on the Twitter platform. The dataset contains recent tweets about Pfizer and BioNTech vaccines. In the context of this research, we have investigated people’s sentiments regarding vaccinations manufactured by Pfizer. Additionally, the dataset required to build this machine -learning model may be downloaded from Kaggle. The tweets acquired from Twitter have been examined using machine learning algorithms to determine the various sentiments that are included within the tweets. The results show 40.9 % of Tweets with positive segments, while 48.9 % with negative and 10.2% seemed neutral. In terms of model performance evaluation, this study has used different ML classification algorithms to see which classifier gives the best model accuracy.