Implementation Paper on Analyzing COVID-19 Vaccines on Twitter Dataset Using Tweepy and Text Blob

Abstract

This paper depends on utilizing twitter for sentiment analysis of the views of people on COVID-19 vaccines and eagerness to have the jab. An ever increasing number of individuals have begun posting on the web about whether they are in favor of these vaccines or not. Many mediums are there which give these analysis among which one such medium is Twitter which has gotten very mainstream as of late. Twitter is a famous microblogging website where clients are permitted a constraint of 280 characters; this sort of limitation causes the clients to be compact just as expressive simultaneously. Thus, it turns into a rich hotspot for opinion examination and belief mining. In this examination, we will investigate the eagerness of having different vaccine by people and their recommendation to others after having the same. In the wake of applying different models and machine learning algorithms to tweets information, we have discovered that it is for sure conceivable to anticipate the vaccine is being favored or not on a large scale.