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: JMIR Medical Informatics

Date Submitted: Jun 29, 2024
Date Accepted: Feb 4, 2025

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

Public Attitudes Toward Violence Against Doctors: Sentiment Analysis of Chinese Users

Zheng Y, Tian M, Chen J, Zhang L, Gao J, Li X, Wen J, Qu X

Public Attitudes Toward Violence Against Doctors: Sentiment Analysis of Chinese Users

JMIR Med Inform 2025;13:e63772

DOI: 10.2196/63772

PMID: 40111382

PMCID: 11969123

Public Attitudes Towards Violence Against Doctors: Sentiment Analysis of Chinese Users

  • Yuwen Zheng; 
  • Meirong Tian; 
  • Jingjing Chen; 
  • Lei Zhang; 
  • Jia Gao; 
  • Xiang Li; 
  • Jin Wen; 
  • Xing Qu

ABSTRACT

Background:

Violence against doctors attracts the public’s attention both online and in the real world. Understanding the change in public opinion is essential to monitor public sentiment and make strategies to comfort the public’s emotions.

Objective:

This study aims to quantify the difference in public sentiment according to online public opinion life cycle theory and describe an evolution of public sentiment during a high-profile violence against doctors’ crisis in China.

Methods:

This study used the term frequency-inverse document frequency (TF-IDF) algorithm to extract key terms and created keyword clouds from textual comments. The Latent Dirichlet Allocation (LDA) topic model was employed to analyze the thematic evolution within public sentiment. The integrated Chinese Sentiment Lexicon was used to analyze the evolution of sentiments in the collected data.

Results:

12,775 valid comments were collected on public opinion on Sina Weibo in China. Thematic and sentiment analyses showed that the public’s sentiments were highly negative during the outbreak period (Disgust: 33.52%, Anger: 22.32%), then smoothly changed to positive and negative during the spread period (Sorrow: 34.45%, Joy: 32.46%), and tended to be rational and peaceful during the decline period (Joy: 32.71%, Sorrow: 27.98%). However, no matter how emotions change, the leading tone of each period contains a large number of negative sentiments.

Conclusions:

This study simultaneously examined the dynamics of theme change and sentiment evolution in crises involving violence against doctors. It discovered that public sentiment varied in tandem with the theme shifts, yet the dominant sentiment from the initial stage of public opinion prevailed throughout. This finding, distinguished from prior research, underscored the enduring impact of initial public sentiment. The results offered valuable insights for medical institutions and authorities, suggesting the need for tailored risk communication strategies responsive to the evolving themes and sentiments at different stages of a crisis.


 Citation

Please cite as:

Zheng Y, Tian M, Chen J, Zhang L, Gao J, Li X, Wen J, Qu X

Public Attitudes Toward Violence Against Doctors: Sentiment Analysis of Chinese Users

JMIR Med Inform 2025;13:e63772

DOI: 10.2196/63772

PMID: 40111382

PMCID: 11969123

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.