Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 24, 2023
Date Accepted: Oct 11, 2023

The final, peer-reviewed published version of this preprint can be found here:

Temporal and Emotional Variations in People’s Perceptions of Mass Epidemic Infectious Disease After the COVID-19 Pandemic Using Influenza A as an Example: Topic Modeling and Sentiment Analysis Based on Weibo Data

Dai J, Lyu F, Yu L, He Y

Temporal and Emotional Variations in People’s Perceptions of Mass Epidemic Infectious Disease After the COVID-19 Pandemic Using Influenza A as an Example: Topic Modeling and Sentiment Analysis Based on Weibo Data

J Med Internet Res 2023;25:e49300

DOI: 10.2196/49300

PMID: 37917144

PMCID: 10654902

Analysis of Temporal and Emotional Variations in People's Perceptions of Mass Epidemic Infectious Disease After the COVID-19 Pandemic: A Study of Information in Weibo Using the Example of Influenza A

  • Jing Dai; 
  • Fang Lyu; 
  • Lin Yu; 
  • Yunyu He

ABSTRACT

Background:

After COVID-19, new mass infectious diseases such as influenza A are spreading and becoming more contagious. The public needs to be sufficiently concerned about mass epidemics to reduce the negative impact of mass epidemics.

Objective:

This study conducted an analysis of 9,111 blog posts related to influenza A, aiming to understand the public's sentiments towards mass epidemic infections in the aftermath of the COVID-19 pandemic. Weibo was selected as the data source, and a statistical analysis was carried out to assess the level of attention across different regions.

Methods:

The collected data underwent LDA topic modeling and BiLSTM models to analyze sentiment.

Results:

The findings indicated a higher number of posts originating from eastern provinces compared to western provinces in China, with inland provinces displaying greater interest in influenza A compared to coastal regions. Women exhibited a higher level of concern than men, and regular users constituted the majority of the user types. Public concerns about influenza A were categorized into 23 topics, with six main topics identified. The overall sentiment expressed by the public leaned predominantly negative (87%), while positive opinions were linked to preventive measures and reliable vaccines. Negative sentiments reflected the concerns and discomfort experienced by individuals.

Conclusions:

These findings underscore the significance of implementing effective prevention and control measures, providing reliable vaccines, and disseminating accurate information to address negative sentiments and bolster public confidence in managing epidemics.


 Citation

Please cite as:

Dai J, Lyu F, Yu L, He Y

Temporal and Emotional Variations in People’s Perceptions of Mass Epidemic Infectious Disease After the COVID-19 Pandemic Using Influenza A as an Example: Topic Modeling and Sentiment Analysis Based on Weibo Data

J Med Internet Res 2023;25:e49300

DOI: 10.2196/49300

PMID: 37917144

PMCID: 10654902

The author of this paper has made a PDF available, but requires the user to login, or create an account.

© 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.