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Exploring the Needs of Elderly Care in China from Family Caregivers’ Perspective via Machine Learning Approaches

Author

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  • Ying Wang

    (Universal Design Institute, Zhejiang Sci-Tech University, Hangzhou 310018, China)

  • Peiwen Luo

    (Universal Design Institute, Zhejiang Sci-Tech University, Hangzhou 310018, China)

Abstract

With the rapid graying of China’s population, ensuring and improving the quality of life for Chinese elderly people has become an urgent issue. This paper explores the needs of elderly people in China from the perspective of their caregivers by applying machine learning approach upon social media posts related to elderly care and subsequently put forward strategies with respect to data mining findings. We obtain more than thirty thousand texts from the Douban discussion group named “One-Child Parent Retirement Exchange”; Latent Dirichlet Allocation (LDA) model is employed to extract topic and words, to analyze and categorize text into relevant elderly care. This study then utilizes SnowNLP module upon previous outcome to appraise the emotional bias of the caregivers. Our finding points out that the essential needs of Chinese elderly people are mental health needs, information needs and intergenerational needs; the emotional bias of children in supporting their parents was generally negative. At the end, our paper subsequently suggests strategies to satisfy the primary elderly caring needs while at the same time alleviating caregivers’ pressure.

Suggested Citation

  • Ying Wang & Peiwen Luo, 2022. "Exploring the Needs of Elderly Care in China from Family Caregivers’ Perspective via Machine Learning Approaches," Sustainability, MDPI, vol. 14(19), pages 1-14, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:11847-:d:920102
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    References listed on IDEAS

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    1. Christine C. Ekenga & Cora-Ann McElwain & Nadav Sprague, 2018. "Examining Public Perceptions about Lead in School Drinking Water: A Mixed-Methods Analysis of Twitter Response to an Environmental Health Hazard," IJERPH, MDPI, vol. 15(1), pages 1-10, January.
    2. Woochun Jun, 2020. "A Study on the Current Status and Improvement of the Digital Divide among Older People in Korea," IJERPH, MDPI, vol. 17(11), pages 1-13, June.
    3. Phoey Lee Teh & Scott Piao & Mansour Almansour & Huey Fang Ong & Abdul Ahad, 2022. "Analysis of Popular Social Media Topics Regarding Plastic Pollution," Sustainability, MDPI, vol. 14(3), pages 1-23, February.
    4. Elisabeth J. Croll, 2006. "The Intergenerational Contract in the Changing Asian Family," Oxford Development Studies, Taylor & Francis Journals, vol. 34(4), pages 473-491.
    5. Scott Deerwester & Susan T. Dumais & George W. Furnas & Thomas K. Landauer & Richard Harshman, 1990. "Indexing by latent semantic analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 391-407, September.
    6. Fengyu Wu, 2022. "Intergenerational Support and Life Satisfaction of Older Parents in China: A Rural–Urban Divide," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 160(2), pages 1071-1098, April.
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