Research on supply characteristics of China's long-term care insurance policy based on text mining
LIU Zhihan
LI Hebin
LU Zhicheng
WANG Xuehan
Abstract：Objective:To explore the key components of long-term care insurance policy in China to provide insights for enhancing the formulation and implementation of future policy documents.Methods:Utilizing the TF-IDF word vector model to conduct text mining research on over 1 600 Chinese long-term care insurance policy documents from the CLIP Database.Results:Using multidimensional scaling analysis,the policy text content was sorted out three policy threads:political promotion,service models and content,and standard formulation.Conclusions:The government needs to innovate institutional supply,encourage data-driven provision,and enhance crisis learning awareness.
Keywords：long-term care insuranceTF-IDF word vector modelmultidimensional scale analysistext miningpolicy provision
Publication Date：2025-10-10
Online Publishing Date：2025-10-10(First online date of this platform, not the publication date of the document)
Pages：14( 3242-3255 )