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

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.