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

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

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Dementia is a global public health priority due to rapid growth of the aging population. As China has the world’s largest population with dementia, this debilitating disease has created tremendous challenges for older adults, family caregivers, and health care systems on the mainland nationwide. However, public awareness and knowledge of the disease remain limited in Chinese society. Objective: This study examines online public discourse and sentiment toward dementia among the Chinese public on a leading Chinese social media platform Weibo. Specifically, this study aims to (1) assess and examine public discourse and sentiment toward dementia among the Chinese public, (2) determine the extent to which dementia-related discourse and sentiment vary among different user groups (ie, government, journalists/news media, scientists/experts, and the general public), and (3) characterize temporal trends in public discourse and sentiment toward dementia among different user groups in China over the past decade. Methods: In total, 983,039 original dementia-related posts published by 347,599 unique users between 2010 and 2021, together with their user information, were analyzed. Machine learning analytical techniques, including topic modeling, sentiment analysis, and semantic network analyses, were used to identify salient themes/topics and their variations across different user groups (ie, government, journalists/news media, scientists/experts, and the general public). Results: Topic modeling results revealed 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 2018. Raising awareness is the least discussed topic over time. Sentiment analysis indicated that Weibo users generally attach negative attitudes/emotions to dementia, with the general public holding a more negative attitude than other user groups. Conclusions: Overall, dementia has received greater public attention on social media since 2018. In particular, discussions related to dementia advocacy and policy are gaining momentum in China. However, disparaging language is still used to describe dementia in China; therefore, a nationwide initiative is needed to alter the public discourse on dementia. The results contribute to previous research by providing a macrolevel understanding of the Chinese public’s discourse and attitudes toward dementia, which is essential for building national education and policy initiatives to create a dementia-friendly society. Our findings indicate that dementia is associated with negative sentiments, and symptoms and prevention dominate public discourse.

Original languageEnglish (US)
Article numbere39805
JournalJournal of medical Internet research
Volume24
Issue number9
DOIs
StatePublished - Sep 1 2022

Keywords

  • aging
  • content analysis
  • dementia
  • elderly population
  • infodemiology
  • machine learning
  • public discourse
  • public discourse
  • sentiment
  • sentiment analysis
  • social media
  • social support
  • thematic analysis
  • topic modeling
  • Weibo

ASJC Scopus subject areas

  • Health Informatics

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