Uncovering Topics Related to COVID-19 Pandemic on Twitter

Han Zheng; Dion Hoe Lian Goh; Edmund Wei Jian Lee; Chei Sian Lee; Yin Leng Theng

doi:10.1007/978-3-030-64452-9_28

Uncovering Topics Related to COVID-19 Pandemic on Twitter

Han Zheng^*, Dion Hoe Lian Goh, Edmund Wei Jian Lee, Chei Sian Lee, Yin Leng Theng

^*Corresponding author for this work

Nanyang Technological University

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

3 Citations (Scopus)

Abstract

The World Health Organization declared COVID-19 as a pandemic on 11 March 2020 due to its rapid spread worldwide. This work-in-progress paper aims to uncover topics related to COVID-19 discussed on Twitter. Using topic modelling, we analyzed two weeks of tweets (11 March–25 March 2020) in English and found 17 latent topics, covering a broad range of issues such as health and economic impact, political and legislative responses, prevention measures, as well as disruption to individuals’ daily lives. The results of this preliminary study show a helpful step to understand public communications about the virus and thus inform health practitioners to propose effective safety measures against COVID-19.

Original language	English
Title of host publication	Digital Libraries at Times of Massive Societal Transition - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings
Editors	Emi Ishita, Natalie Lee Pang, Lihong Zhou
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	307-312
Number of pages	6
ISBN (Print)	9783030644512
DOIs	https://doi.org/10.1007/978-3-030-64452-9_28
Publication status	Published - 2020
Externally published	Yes
Event	22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020 - Kyoto, Japan Duration: Nov 30 2020 → Dec 1 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12504 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020
Country/Territory	Japan
City	Kyoto
Period	11/30/20 → 12/1/20

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

ASJC Scopus Subject Areas

Theoretical Computer Science
General Computer Science

Keywords

COVID-19
Topic modelling
Tweets

Access to Document

10.1007/978-3-030-64452-9_28

Cite this

Zheng, H., Goh, D. H. L., Lee, E. W. J., Lee, C. S., & Theng, Y. L. (2020). Uncovering Topics Related to COVID-19 Pandemic on Twitter. In E. Ishita, N. L. Pang, & L. Zhou (Eds.), Digital Libraries at Times of Massive Societal Transition - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings (pp. 307-312). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12504 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-64452-9_28

Zheng, Han ; Goh, Dion Hoe Lian ; Lee, Edmund Wei Jian et al. / Uncovering Topics Related to COVID-19 Pandemic on Twitter. Digital Libraries at Times of Massive Societal Transition - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings. editor / Emi Ishita ; Natalie Lee Pang ; Lihong Zhou. Springer Science and Business Media Deutschland GmbH, 2020. pp. 307-312 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{5f8cea2a69fc4a76ba5e5164018e8d8a,

title = "Uncovering Topics Related to COVID-19 Pandemic on Twitter",

abstract = "The World Health Organization declared COVID-19 as a pandemic on 11 March 2020 due to its rapid spread worldwide. This work-in-progress paper aims to uncover topics related to COVID-19 discussed on Twitter. Using topic modelling, we analyzed two weeks of tweets (11 March–25 March 2020) in English and found 17 latent topics, covering a broad range of issues such as health and economic impact, political and legislative responses, prevention measures, as well as disruption to individuals{\textquoteright} daily lives. The results of this preliminary study show a helpful step to understand public communications about the virus and thus inform health practitioners to propose effective safety measures against COVID-19.",

keywords = "COVID-19, Topic modelling, Tweets",

author = "Han Zheng and Goh, {Dion Hoe Lian} and Lee, {Edmund Wei Jian} and Lee, {Chei Sian} and Theng, {Yin Leng}",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020 ; Conference date: 30-11-2020 Through 01-12-2020",

year = "2020",

doi = "10.1007/978-3-030-64452-9_28",

language = "English",

isbn = "9783030644512",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "307--312",

editor = "Emi Ishita and Pang, {Natalie Lee} and Lihong Zhou",

booktitle = "Digital Libraries at Times of Massive Societal Transition - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings",

address = "Germany",

}

Zheng, H, Goh, DHL, Lee, EWJ, Lee, CS & Theng, YL 2020, Uncovering Topics Related to COVID-19 Pandemic on Twitter. in E Ishita, NL Pang & L Zhou (eds), Digital Libraries at Times of Massive Societal Transition - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12504 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 307-312, 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Kyoto, Japan, 11/30/20. https://doi.org/10.1007/978-3-030-64452-9_28

Uncovering Topics Related to COVID-19 Pandemic on Twitter. / Zheng, Han; Goh, Dion Hoe Lian; Lee, Edmund Wei Jian et al.
Digital Libraries at Times of Massive Societal Transition - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings. ed. / Emi Ishita; Natalie Lee Pang; Lihong Zhou. Springer Science and Business Media Deutschland GmbH, 2020. p. 307-312 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12504 LNCS).

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

TY - GEN

T1 - Uncovering Topics Related to COVID-19 Pandemic on Twitter

AU - Zheng, Han

AU - Goh, Dion Hoe Lian

AU - Lee, Edmund Wei Jian

AU - Lee, Chei Sian

AU - Theng, Yin Leng

PY - 2020

Y1 - 2020

N2 - The World Health Organization declared COVID-19 as a pandemic on 11 March 2020 due to its rapid spread worldwide. This work-in-progress paper aims to uncover topics related to COVID-19 discussed on Twitter. Using topic modelling, we analyzed two weeks of tweets (11 March–25 March 2020) in English and found 17 latent topics, covering a broad range of issues such as health and economic impact, political and legislative responses, prevention measures, as well as disruption to individuals’ daily lives. The results of this preliminary study show a helpful step to understand public communications about the virus and thus inform health practitioners to propose effective safety measures against COVID-19.

AB - The World Health Organization declared COVID-19 as a pandemic on 11 March 2020 due to its rapid spread worldwide. This work-in-progress paper aims to uncover topics related to COVID-19 discussed on Twitter. Using topic modelling, we analyzed two weeks of tweets (11 March–25 March 2020) in English and found 17 latent topics, covering a broad range of issues such as health and economic impact, political and legislative responses, prevention measures, as well as disruption to individuals’ daily lives. The results of this preliminary study show a helpful step to understand public communications about the virus and thus inform health practitioners to propose effective safety measures against COVID-19.

KW - COVID-19

KW - Topic modelling

KW - Tweets

UR - http://www.scopus.com/inward/record.url?scp=85097545664&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85097545664&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-64452-9_28

DO - 10.1007/978-3-030-64452-9_28

M3 - Conference contribution

AN - SCOPUS:85097545664

SN - 9783030644512

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 307

EP - 312

BT - Digital Libraries at Times of Massive Societal Transition - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings

A2 - Ishita, Emi

A2 - Pang, Natalie Lee

A2 - Zhou, Lihong

PB - Springer Science and Business Media Deutschland GmbH

T2 - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020

Y2 - 30 November 2020 through 1 December 2020

ER -

Zheng H, Goh DHL, Lee EWJ, Lee CS , Theng YL. Uncovering Topics Related to COVID-19 Pandemic on Twitter. In Ishita E, Pang NL, Zhou L, editors, Digital Libraries at Times of Massive Societal Transition - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 307-312. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-64452-9_28

Uncovering Topics Related to COVID-19 Pandemic on Twitter

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus Subject Areas

Keywords

Access to Document

Other files and links

Fingerprint

Cite this