A Warning System for the Return of COVID-19 Using Social Media Data

Shan Shan; Yulei Li

doi:10.1109/ICDABI51230.2020.9325668

A Warning System for the Return of COVID-19 Using Social Media Data

Shan Shan, Yulei Li

Computer and Information Sciences Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Epidemic research can be enhanced through the use of social media data, an authoritative new data source that can not only be used to identify an epidemic and track the path of a disease but also for risk assessment and analysis. Existing research generally focuses on tracking tasks and epidemic types, but the relationship between applicable tasks and technical methods is rarely considered. In contrast, this research summarises the characteristics of social media data, emphasizing data and method dependencies, while identifying the processing methods used for diverse epidemic warning tasks. This work provides a reference for the application of social media data in epidemic research as well as a warning system for the return of COVID-19.

Original language	English
Title of host publication	2020 International Conference on Data Analytics for Business and Industry
Subtitle of host publication	Way Towards a Sustainable Economy, ICDABI 2020
Place of Publication	Piscataway, US
Publisher	IEEE
Pages	45-49
Number of pages	5
ISBN (Electronic)	9781728196756
ISBN (Print)	9781728196763
DOIs	https://doi.org/10.1109/ICDABI51230.2020.9325668
Publication status	Published - 26 Oct 2020
Event	2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020 - Sakheer, Bahrain Duration: 26 Oct 2020 → 27 Oct 2020

Conference

Conference	2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020
Country/Territory	Bahrain
City	Sakheer
Period	26/10/20 → 27/10/20

Keywords

continued learning
coronavirus warning
COVID-19
epidemic research
social media data

Access to Document

10.1109/ICDABI51230.2020.9325668

Cite this

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title = "A Warning System for the Return of COVID-19 Using Social Media Data",

abstract = "Epidemic research can be enhanced through the use of social media data, an authoritative new data source that can not only be used to identify an epidemic and track the path of a disease but also for risk assessment and analysis. Existing research generally focuses on tracking tasks and epidemic types, but the relationship between applicable tasks and technical methods is rarely considered. In contrast, this research summarises the characteristics of social media data, emphasizing data and method dependencies, while identifying the processing methods used for diverse epidemic warning tasks. This work provides a reference for the application of social media data in epidemic research as well as a warning system for the return of COVID-19.",

keywords = "continued learning, coronavirus warning, COVID-19, epidemic research, social media data",

author = "Shan Shan and Yulei Li",

year = "2020",

month = oct,

day = "26",

doi = "10.1109/ICDABI51230.2020.9325668",

language = "English",

isbn = "9781728196763",

pages = "45--49",

booktitle = "2020 International Conference on Data Analytics for Business and Industry",

publisher = "IEEE",

address = "United States",

note = "2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020 ; Conference date: 26-10-2020 Through 27-10-2020",

}

Shan, S & Li, Y 2020, A Warning System for the Return of COVID-19 Using Social Media Data. in 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020., 9325668, IEEE, Piscataway, US, pp. 45-49, 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020, Sakheer, Bahrain, 26/10/20. https://doi.org/10.1109/ICDABI51230.2020.9325668

TY - GEN

T1 - A Warning System for the Return of COVID-19 Using Social Media Data

AU - Shan, Shan

AU - Li, Yulei

PY - 2020/10/26

Y1 - 2020/10/26

N2 - Epidemic research can be enhanced through the use of social media data, an authoritative new data source that can not only be used to identify an epidemic and track the path of a disease but also for risk assessment and analysis. Existing research generally focuses on tracking tasks and epidemic types, but the relationship between applicable tasks and technical methods is rarely considered. In contrast, this research summarises the characteristics of social media data, emphasizing data and method dependencies, while identifying the processing methods used for diverse epidemic warning tasks. This work provides a reference for the application of social media data in epidemic research as well as a warning system for the return of COVID-19.

AB - Epidemic research can be enhanced through the use of social media data, an authoritative new data source that can not only be used to identify an epidemic and track the path of a disease but also for risk assessment and analysis. Existing research generally focuses on tracking tasks and epidemic types, but the relationship between applicable tasks and technical methods is rarely considered. In contrast, this research summarises the characteristics of social media data, emphasizing data and method dependencies, while identifying the processing methods used for diverse epidemic warning tasks. This work provides a reference for the application of social media data in epidemic research as well as a warning system for the return of COVID-19.

KW - continued learning

KW - coronavirus warning

KW - COVID-19

KW - epidemic research

KW - social media data

UR - http://www.scopus.com/inward/record.url?scp=85100448358&partnerID=8YFLogxK

U2 - 10.1109/ICDABI51230.2020.9325668

DO - 10.1109/ICDABI51230.2020.9325668

M3 - Conference contribution

AN - SCOPUS:85100448358

SN - 9781728196763

SP - 45

EP - 49

BT - 2020 International Conference on Data Analytics for Business and Industry

PB - IEEE

CY - Piscataway, US

T2 - 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020

Y2 - 26 October 2020 through 27 October 2020

ER -

A Warning System for the Return of COVID-19 Using Social Media Data

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