COVID19α: Interactive Spatio-Temporal Visualization of COVID-19 Symptoms through Tweet Analysis

ABSTRACTIn this demo, we focus on analyzing COVID-19 related symptoms across the globe reported through tweets by building an interactive spatio-temporal visualization tool, i.e., COVID19α. Using around 462 million tweets collected over a span of six months, COVID19α provides three different types of visualization tools: 1) Spatial Visualization with a focus on visualizing COVID-19 symptoms across different geographic locations; 2) Temporal Visualization with a focus on visualizing the evolution of COVID-19 symptoms over time for a particular geographic location; and 3) Spatio-Temporal Visualization with a focus on combining both spatial and temporal analysis to provide comparative visualizations between two (or more) symptoms across time and space. We believe that health professionals, scientists, and policymakers will be able to leverage this interactive tool to devise better and targeted health intervention policies. Our developed interactive visualization tool is publicly available at https://bijoy-sust.github.io/Covid19/.