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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 24, 2022
Date Accepted: Jul 23, 2022

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

Public Discourse and Sentiment Toward Dementia on Chinese Social Media: Machine Learning Analysis of Weibo Posts

Kong D, Chen A, Zhang J, Xiang X, Lou WV, Kwok T, Wu B

Public Discourse and Sentiment Toward Dementia on Chinese Social Media: Machine Learning Analysis of Weibo Posts

J Med Internet Res 2022;24(9):e39805

DOI: 10.2196/39805

PMID: 36053565

PMCID: 9482068

Public Discourse and Sentiment Toward Dementia on Chinese Social Media: Findings From a Machine Learning Analysis

  • Dexia Kong; 
  • Anfan Chen; 
  • Jingwen Zhang; 
  • Xiaoling Xiang; 
  • W.Q. Vivian Lou; 
  • Timothy Kwok; 
  • Bei Wu

ABSTRACT

Background:

Dementia is a global public health priority due to the rapid growth of the aging population. With the world’s largest dementia population, this debilitating disease has brought tremendous challenges to older adults, family caregivers, and healthcare systems in mainland China. However, public awareness and knowledge of the disease remain very limited in Chinese society.

Objective:

This study aims to examine online public discourse and sentimentality of dementia among the Chinese public on a leading Chinese social media platform (i.e., Sina Weibo).

Methods:

A total of 983,039 original dementia-related posts published by 347,599 unique users between 2010 and 2021, together with their user information, were analyzed. Text mining analytic techniques, including topic modeling, sentiment analysis, and sematic network analyses, were performed to identify salient themes/topics and their variations across different user groups (i.e., government; journalists/news media; scientists/experts; and the general public).

Results:

Topic modeling results reveal that symptoms, prevention, and social support are the most prevalent dementia-related themes on Weibo. Posts about dementia policy/advocacy have been increasing in volume since 2019. Raising awareness is the least discussed topic over time. Sentiment analyses show that Weibo users generally attach negative tones/emotions toward dementia, with the general public holding a more negative tone compared to other user groups.

Conclusions:

Overall, dementia has been gaining increased public attention on social media since 2018. Particularly, discussions related to dementia advocacy and policy are gaining momentum in China. The findings suggest that there is a great need to raise awareness of dementia in general public. Overall, the sentiment towards dementia is negative on social media, especially among the general public users. Social media platforms could be a potential platform that could be leveraged for future dementia education interventions to build dementia-friendly communities.


 Citation

Please cite as:

Kong D, Chen A, Zhang J, Xiang X, Lou WV, Kwok T, Wu B

Public Discourse and Sentiment Toward Dementia on Chinese Social Media: Machine Learning Analysis of Weibo Posts

J Med Internet Res 2022;24(9):e39805

DOI: 10.2196/39805

PMID: 36053565

PMCID: 9482068

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