In this project, we are going through the Twitter Sentiment Analysis problem, in relation to what people think about the Covid-19 vaccination, which we will solve using the concepts of Natural Language Processing (NLP). Natural language is the language we all talk in. It could be Hindi, English, Spanish, or anything. And when we talk about natural language processing, we basically refer to making computers able to process this language, and more importantly understand it and take actions based on it. Now this language can be text-based or audio-based. Our Google Voice assistant, Siri, and even google translator are excellent examples of this. We are going to build a machine learning model that is able to analyse loads of Twitter tweets and be able to judge the sentiments behind the tweets. Our project presents a general overview of how people in different regions of the same country are satisfied or dissatisfied with the vaccine. Our project will show, among India and America, the impact of the Vaccine and give an idea about what the people in that area think about the Vaccine namely in four categories - POSITIVE, NEGATIVE and NEUTRAL. This classification is done by extracting Twitter data with its latitude and longitude. We will also create an interactive map with pop-up and zoom features for better visualisation. We are gonna be analysing tweets made against the "Covid-19 vaccination". These types of models can be used by Twitter and Facebook and other social media platforms to filter out hate speeches, unwanted comments, or other fake rumours on their platforms. These models are extremely essential to curb negative influence which might subconsciously affect the minds of people.
