Sentiment Analysis on COVID-19 Tweeter Dataset

ABSTRACT

Everyone is aware about coronavirus disease (in short it is COVID-19). The meaning of word COVID is defined as ‘CO’ stands for corona, ‘VI’ for virus, and ‘D’ for disease. It is an infectious disease caused by a newly discovered coronavirus which makes all countries on globe unstable. More than 206 countries is affected due to this COVID-19, and more than 110,00,000 people infected on the globe, and out of that more than 5,00,000 people died due to this incurable (till date no vaccination) disease. So that COVID-19 is declared pandemic. In this research, generic social media dataset related to COVID-19 is used for study and find sentiment analysis. In this article, twitter data collection, data preprocessing, and calculation of tweeter sentiment analysis were discussed in detail with respect to India and USA and whole world. Different Python libraries were discussed in this article. During 3 months, first 2 months, USA was more positive comparison to India and world. But, after lockdown in June, India is more positive compared to USA and world. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.