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

The world has seen an unprecedented catastrophe since January 2020 due to the COVID-19 pandemic costing more than one million human lives. Global efforts were taken to develop vaccines leading to many ongoing clinical trials in different countries around the world to investigate the way the human body exhibits various COVID-19 related symptoms under different conditions. In this demo, we focus on analyzing COVID-19 related symptoms across the globe reported through tweets by building an interactive spatiotemporal 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.

Spatial Visualization

This component focuses on visualizing COVID-19 symptoms across different geographic locations. COVID19α provides two types of spatial visualizations:

Twitter Word Cloud: Comparative WordCloud Visualization between two geographic locations.

Clustered Symptom Map: Multi-level granularity based spatial distribution of COVID-19 symptoms through an interactive map interface.

Temporal Visualization

This component presents the visualization of the time-series of COVID-19 symptoms for a particular geographic location. COVID19α provides users with options to create visualizations for a specific subset of symptoms depending on their interests, allowing them to see those symptoms’ evolution patterns over time:

Dynamic Temporal Simulation: Bar Chart Visualization of worldwide symptom distribution over time.

Time-series Map: Multi-level granularity based spatial distribution of COVID-19 symptoms through an interactive map interface.

  • All Tweets: The map contains time series plots of all covid-19 related tweets for different locations.

  • All Symptoms: The map contains time series plots of all covid-19 ‘symptom-tweets’ for different locations.

  • Individual Symptom: The map contains time series plots of ‘symptom-tweets’ of a particular covid-19 symptom.


Spatio-Temporal Visualization

The third and last component of COVID19α combines both spatial and temporal analysis to provide comparative visualizations between two countries or two symptoms:

Spatio-Temporal Evolution between Two Symptoms: Comparative Bar Chart Visualization of affected countries over time between two symptoms.

Temporal Evolution of Symptoms between Two Countries: Comparative Bar Chart Visualization of symptom distribution over time between the two selected countries.