Tweet Data Analysis on COVID-19 Outbreak

Laxmi Narasamma, V.; Sreedevi, M.; Vijay Kumar, G.

COVID-19 outbreak as a pandemic in the month of March 2020 announced by World Health Organization and this pandemic virus was originated from Dragon country China, it is a big pandemic virus has been attacking through out of the world and killing lakhs of people. While this pandemic has persevered to have impact on the lives of many thousands of people, various countries have depended on complete lockdown. During this pandemic circumstance, i.e., in lockdown, individuals around the globe have taken long range interpersonal communication destinations or applications to convey their emotions and discover a way to remain quiet themselves as down. In this work, fleeting supposition investigation coronavirus tweets after some time April 16 to April 13 are appeared. The extremity score of each tweet with VADER calculation in NLP is predominantly engaged in this work. The scores are isolated dependent on compound extremity esteem at last tweets are distinguished into three significant assessment classes like positive, negative and impartial and by demonstrating feeling score plot, fleeting assumptions after some time the information perception is additionally accomplished in this work. This work also focuses data visualization by showing sentiment score plot. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.