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

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Shubhra Kanti Karmaker SantuAuthors Info & Claims

IUI '21 Companion: Companion Proceedings of the 26th International Conference on Intelligent User Interfaces

Pages 28 - 30

https://doi.org/10.1145/3397482.3450715

Published: 14 April 2021 Publication History

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Abstract

In 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/.

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Cited By

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Sufi F(2023)A New Social Media Analytics Method for Identifying Factors Contributing to COVID-19 Discussion TopicsInformation10.3390/info1410054514:10(545)Online publication date: 5-Oct-2023
https://doi.org/10.3390/info14100545
Sarkar SBijoy BSaba SFeng DMahajan YAmin MIslam SKarmaker (“Santu”) S(2023)Ad-Hoc Monitoring of COVID-19 Global Research Trends for Well-Informed Policy MakingACM Transactions on Intelligent Systems and Technology10.1145/357690114:2(1-28)Online publication date: 21-Feb-2023
https://dl.acm.org/doi/10.1145/3576901
Tao YYang CWang TColtey EJin YLiu YJiang RFan ZSong XShibasaki RChen SShyu MLuis S(2022)A Survey on Data-driven COVID-19 and Future Pandemic ManagementACM Computing Surveys10.1145/354281855:7(1-36)Online publication date: 15-Dec-2022
https://dl.acm.org/doi/10.1145/3542818
Show More Cited By

Index Terms

COVID19α: Interactive Spatio-Temporal Visualization of COVID-19 Symptoms through Tweet Analysis
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
2. Information systems
  1. Information systems applications

Index terms have been assigned to the content through auto-classification.

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Published In

IUI '21 Companion: Companion Proceedings of the 26th International Conference on Intelligent User Interfaces

April 2021

101 pages

ISBN:9781450380188

DOI:10.1145/3397482

Co-chairs:
Katrien Verbert
Katholieke Universiteit Leuven
,
Dennis Parra
Pontificia Universidad Católica de Chile
,
General Chair:
Tracy Hammond
Texas A&M University
,
Program Chairs:
Bart Knijnenburg
Clemson University
,
John O'Donovan
UC Santa Barbara
,
Paul Taele
Texas A&M University

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 14 April 2021

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IUI '21: 26th International Conference on Intelligent User Interfaces

April 14 - 17, 2021

TX, College Station, USA

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Sufi F(2023)A New Social Media Analytics Method for Identifying Factors Contributing to COVID-19 Discussion TopicsInformation10.3390/info1410054514:10(545)Online publication date: 5-Oct-2023
https://doi.org/10.3390/info14100545
Sarkar SBijoy BSaba SFeng DMahajan YAmin MIslam SKarmaker (“Santu”) S(2023)Ad-Hoc Monitoring of COVID-19 Global Research Trends for Well-Informed Policy MakingACM Transactions on Intelligent Systems and Technology10.1145/357690114:2(1-28)Online publication date: 21-Feb-2023
https://dl.acm.org/doi/10.1145/3576901
Tao YYang CWang TColtey EJin YLiu YJiang RFan ZSong XShibasaki RChen SShyu MLuis S(2022)A Survey on Data-driven COVID-19 and Future Pandemic ManagementACM Computing Surveys10.1145/354281855:7(1-36)Online publication date: 15-Dec-2022
https://dl.acm.org/doi/10.1145/3542818
Sarkar SKarmaker S(2022)Concept Annotation from Users Perspective: A New ChallengeCompanion Proceedings of the Web Conference 202210.1145/3487553.3524933(1180-1188)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3487553.3524933

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Recommendations

Using treemaps for variable selection in spatio-temporal visualisation

Interactive Data Visualization to Understand Data Better: Case Studies in Healthcare System

An Interactive Visualization Tool to Explore People’s Tweets towards COVID-19

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