Public perception on active aging after COVID-19: an unsupervised machine learning analysis of 44,343 posts

Front Public Health. 2024 Mar 7:12:1329704. doi: 10.3389/fpubh.2024.1329704. eCollection 2024.

Abstract

Introduction: To analyze public perceptions of active aging in China on mainstream social media platforms to determine whether the "14th Five Year Plan for the Development of the Aging Career and Older Adult Care System" issued by the CPC in 2022 has fully addressed public needs.

Methods: The original tweets posted on Weibo between January 1, 2020, and June 30, 2022, containing the words "aging" or "old age" were extracted. A bidirectional encoder representation from transformers (BERT)-based model was used to generate themes related to this perception. A qualitative thematic analysis and an independent review of the theme labels were conducted by the researchers.

Results: The findings indicate that public perceptions revolved around four themes: (1) health prevention and protection, (2) convenient living environments, (3) cognitive health and social integration, and (4) protecting the rights and interests of the older adult.

Discussion: Our study found that although the Plan aligns with most of these themes, it lacks clear planning for financial security and marital life.

Keywords: BERTopic; active aging; policy making; public perception; topic modeling.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • COVID-19* / psychology
  • Humans
  • Public Opinion
  • SARS-CoV-2
  • Social Media*
  • Unsupervised Machine Learning

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research was supported by 2023 Wenzhou Philosophy and Social Science Planning Annual Project (23WSK121YBM) and 2021 The Educational Science Planning Project of Zhejiang Province (2021SCG166).