TweetCOVID: A System for Analyzing Public Sentiments and Discussions about COVID-19 via Twitter Activities
This work addresses the need for real-time public sentiment analysis during the COVID-19 pandemic, but it is incremental as it applies existing methods to new data without introducing novel techniques.
The researchers tackled the problem of understanding public reactions to the COVID-19 pandemic by developing the TweetCOVID system, which analyzes sentiments, emotions, topics, and discussions from Twitter data over time and locations, and demonstrated its usefulness through three example use cases.
The COVID-19 pandemic has created widespread health and economical impacts, affecting millions around the world. To better understand these impacts, we present the TweetCOVID system that offers the capability to understand the public reactions to the COVID-19 pandemic in terms of their sentiments, emotions, topics of interest and controversial discussions, over a range of time periods and locations, using public tweets. We also present three example use cases that illustrates the usefulness of our proposed TweetCOVID system.