On The Use Of Aspect-based Sentiment Analysis Of Twitter Data To Explore The Experiences Of African Americans During Covid-19

This article examines the use of Natural Language Processing (NLP) to analyze the mental and emotional impacts of COVID-19 in the US during the period of January 2020. It looks at the use of topic modeling and sentiment analysis to identify key topics of discussion and the correlation between real-world events and peaks in the number of positive COVID-19 cases. It also looks at the use of NLP to prototype a country-specific early warning system to assist policymakers.