JDR Vol.15 No.4 pp. 530-533
doi: 10.20965/jdr.2020.p0530


Trends of Tweets on the Coronavirus Disease-2019 (COVID-19) Pandemic

Natt Leelawat*,**,†, Jing Tang**,***, Kumpol Saengtabtim*, and Ampan Laosunthara**

*Department of Industrial Engineering, Faculty of Engineering, Chulalongkorn University
Phayathai Road, Pathumwan, Bangkok 10330, Thailand

Corresponding author

**Disaster and Risk Management Information Systems Research Group, Chulalongkorn University, Bangkok, Thailand

***International School of Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand

March 14, 2020
May 10, 2020
June 1, 2020
COVID-19, novel Coronavirus 2019, social networking services, quantitative text analysis, Twitter

The Severe Acute Respiratory Syndrome Coronavirus 2 is a virus causing the COVID-19 pandemic around the world. The World Health Organization (WHO) raised it to the highest level of global alert. The English, Chinese, and Japanese language Twitter data related to this disease during the first period after the WHO started releasing the situation reports were collected and compared with the tweet trends. This study also used quantitative text analysis to extract and analyze the co-occurrence network of English tweets. The findings show that trends and public concerns in social media are related to the breaking news and global trends such as the confirmed cases, the reported death tolls, the quarantined cruise news, the informer, etc.

Cite this article as:
N. Leelawat, J. Tang, K. Saengtabtim, and A. Laosunthara, “Trends of Tweets on the Coronavirus Disease-2019 (COVID-19) Pandemic,” J. Disaster Res., Vol.15 No.4, pp. 530-533, 2020.
Data files:
  1. [1] [accessed February 28, 2020]
  2. [2] N. Leelawat, A. Suppasri, P. Latcharote, and F. Imamura, “The evacuation of Thai citizens during Japan’s 2016 Kumamoto earthquakes: An ICT perspective,” J. Disaster Res., Vol.12, No.sp, pp. 669-677, 2017.
  3. [3] K. Meechang, N. Leelawat, J. Tang, A. Kodaka, and C. Chintanapakdee, “The acceptance of using technology for disaster risk management: A systematic review,” Eng. J., Vol.24, No.4, 2020.
  4. [4] S. Sato and F. Imamura, “An analysis of tweet data tagged with “#Rescue” in the 2017 North Kyushu heavy rain disaster,” J. Jpn. Soc. Nat. Disaster Sci., Vol.37, No.1, pp. 93-102, 2018 (in Japanese with English abstract).
  5. [5] E. M. Glowachki, A. J. Lazard, G. B. Wilcox, M. Mackert, and J. M. Bernhardt, “Identifying the public’s concerns and the Centers for Disease Control and Prevention’s reactions during a health crisis: An analysis of a Zika live Twitter chat,” Am. J. Infect. Control, Vol.44, No.12, pp. 1709-1711, 2016.
  6. [6] A. J. Lazard, E. Scheinfeld, J. M. Bernhardt, G. B. Wilcox, and M. Suran, “Detecting themes pf public concern: A text mining analysis of the centers of disease control and prevention’s Ebola live Twitter chat,” Am. J. Infect. Control, Vol.43, No.10, pp. 1109-1111, 2015.
  7. [7] [accessed March 5, 2020]
  8. [8] K. Higuchi, “KH Coder 3,” [accessed February 21, 2020]
  9. [9] [accessed March 5, 2020]
  10. [10] O. Murao and H. Sakaba, “Quantitative text analysis of Sendai Framework for Disaster Risk Reduction 2015–2030,” J. Disaster Res., Vol.11, No.3, pp. 459-469, 2016.
  11. [11] Y. Ji, Z. Ma, M. P. Peppelenbosch, and Q. Pan, “Potential association between COVID-19 mortality and health-care resource availability,” The Lancet Global Health, Vol.8, No.4, doi: 10.1016/S2214-109X(20)30068-1, 2020.
  12. [12] A. Green, “Li Wenliang,” The Lancet, Vol.395, No.10225, p. 682, doi: 10.1016/S0140-6736(20)30382-2, 2020.
  13. [13] M. Chinazzi, J. T. Davis, M. Ajelli, C. Gioannini, M. Litvinova, S. Merler, A. P. Piontti, K. Mu, L. Rossi, K. Sun, C. Viboud, X. Xiong, H. Yu, M. E. Halloran, I. M. Longini, Jr., and A. Vespignani, “The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak,” Science, Vol.368, No.6489, pp. 395-400, doi: 10.1126/science.aba9757, 2020.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Jul. 19, 2024