ANALYSIS OF TWITTER DATA TO UNDERSTAND COVID-19 TRENDS

Abstract

The spread of the Coronavirus is a matter of great concern to all people worldwide, and the spread of diseases, in general, is worrying due to its psychological and health impact on society. To track these diseases, there are several methods, including the traditional one, which is an examination by the doctor, and there are electronic methods and the use of data analysis from social media, especially Twitter, in our study. Social media is full of huge amounts of data on a daily basis, and people often write about their daily situations and their feelings. This research aims to analyze people’s feelings regarding what they write about the Coronavirus. We were able to build a machine learning model for classifying text tweets. The project contained data estimated at 10,000 tweets during the Corona period to know people’s psychological and physical impact, and the researcher was required to classify them according to the labels in the data provided to the researcher. Twitter and social media data have proven that they can be a medical monitor for symptoms and discover medical and psychological syndromes.