Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Monday, March 11, 2019 at 4:00 PM to 4:30 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?


Currently submitted to: Journal of Medical Internet Research

Date Submitted: May 19, 2020
Open Peer Review Period: May 19, 2020 - Jul 14, 2020
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Application of the Online Big Data Platform in Monitoring Chinese Public Attention to the Outbreak of COVID-19

  • Mengchi Hou; 
  • Xue Gong; 
  • Rui Guo; 
  • Yangyang Han; 



The outbreak of the COVID-19 epidemic in 2019 exerted an enormous global public reaction.


The online big data reflects public attention of hot issues. This study aimed to use the Baidu Index (BDI) and Sina Micro Index (SMI) to confirm the primitive correlation between COVID-19 related data and Chinese online data.


Bivariate correlation statistics was used to check the relationship between epidemic trends of the BDI and SMI, and identify the difference of public concerns about COVID-19 between the epidemic area (Hubei province) and non-epidemic area (all other provinces).


The public's usage trend of the Baidu search engine and Sina Weibo was consistent during the COVID-19 outbreak (Pearson correlation coefficient =0.807, P<0.001). But compared with the SMI, the BDI was more closely related to the actual epidemic. The BDI and SMI had correlations with new confirmed cases (P<0.01), cumulative confirmed cases (P<0.01), cumulative death cases (P<0.01), new cured discharged cases (P<0.01), and cumulative cured discharged cases (P<0.01), but not with new death cases. Besides, the public's demand for information on COVID-19 was consistent and urgent across the country (Spearman correlation coefficient=0.930, P<0.001), regardless of the location of the epidemic area.


The public paid more attention to indicators of confirmed cases due to numerous irresistible factors and cured circumstances with positive outcomes. But the public had a lag in the attention of COVID-19 in the non-epidemic area. In the risk communication of public health emergencies, relevant departments can effectively use the information dissemination characteristics of the Baidu search engine and Sina Weibo, to convey front-line information to the public timely and accurately, and improve the effectiveness of risk communication.


Please cite as:

Hou M, Gong X, Guo R, Han Y

Application of the Online Big Data Platform in Monitoring Chinese Public Attention to the Outbreak of COVID-19

JMIR Preprints. 19/05/2020:20475

DOI: 10.2196/preprints.20475


Download PDF

Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.