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Published on: July 27, 2018
Public perception on active aging after COVID-19: an unsupervised machine learning analysis of 44,343 posts
Peipei Chen1, Yuwei Jin1, Xinfang Ma1
1School of Foreign Language Studies, Wenzhou Medical University, Wenzhou, Zhejiang, China.
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.
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