Introduction: The traditional family responsibility system faces challenges as China undergoes rapid demographic shifts with an increasingly older population. Recognizing the potential of market-driven senior care, Continuing Care Retirement Communities (CCRCs) have emerged as a significant alternative. However, cultural stigmas and concerns about the quality, services, and health of older adults in these facilities raise questions over their broad acceptance.
Methods: This study examines public sentiment toward CCRCs through sentiment analysis of 1,027,295 pre-processed Weibo posts. Utilizing Natural Language Processing (NLP) combined with fine-grained sentiment analysis and the Term Frequency-Inverse Document Frequency algorithm, the attitudes and emotions reflected in each data point are analyzed, identifying key contributing factors, and exploring the underlying reasons.
Results And Discussion: The results reveal a predominantly positive sentiment toward CCRCs, emphasizing factors such as the living environment and government involvement. However, areas of concern, such as potential fraud and health and safety issues, remain. These findings both shed light on the public's acceptance or resistance to CCRCs for stakeholders and highlight the potential of social media analysis in shaping older people's care perceptions in today's China.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11875845 | PMC |
| http://dx.doi.org/10.3389/fpubh.2024.1454287 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Tripartite Game Analysis of Online Public Opinion Evolution in Major Epidemics in the Context of Life Sciences.
SLAS Technol
March 2025
Business School, University of Shanghai for Science and Technology, 200093, Shanghai, China. Electronic address:
In the face of a sudden major epidemic, people's panic may likely lead to the disruption of the public opinion ecosystem and the disorder of public opinion order. Therefore, clarifying the key main bodies and mechanisms in governing online public opinion is of crucial significance for effectively managing and guiding it. Firstly, based on the sentiment analysis of opinion leaders, an evolutionary game model involving the government, netizens, and opinion leaders was constructed.
View Article and Find Full Text PDFResearch on the Chinese capital culture perception based on Weibo big data.
Heliyon
February 2025
College of Applied Arts and Science, Beijing Union University, Beijing, 100191, China.
Ancient capital culture, red culture, Beijing-style culture, and innovation culture together constitute the capital's cultural system of China and support Beijing's position as the Chinese cultural center. In order to better help the cultural construction of the capital, Beijing, and to find some common and reasonable ways to reconcile the complex urban cultural system, this paper is based on the Weibo data of Beijing in 2019, takes the BERT pre-training model and the newer topic model "BERTopic" as the tools, combines the text content, spatial layout, and sentiment analysis methods, and explores the public perception of four types of capital culture in Beijing. The results reveal that: (1) Although the perception level of Dongcheng, Xicheng, Haidian and Chaoyang core areas is much higher than that of remote areas, the sentiment feedback of remote areas is better than that of the former; (2) A type of culture actively introduces other cultural types or even foreign cultural elements in the system, which helps it form a unique cultural attraction.
View Article and Find Full Text PDFLeveraging LLaMA2 for improved document classification in English.
PeerJ Comput Sci
February 2025
School of Foreign Languages, Taizhou University, Taizhou City, Jiangsu Province, China.
Document classification is an important component of natural language processing, with applications that include sentiment analysis, content recommendation, and information retrieval. This article investigates the potential of Large Language Model Meta AI (LLaMA2), a cutting-edge language model, to enhance document classification in English. Our experiments show that LLaMA2 outperforms traditional classification methods, achieving higher precision and recall values on the WOS-5736 dataset.
View Article and Find Full Text PDFA majority voting framework for reliable sentiment analysis of product reviews.
PeerJ Comput Sci
February 2025
Business Information Systems, Babes-Bolyai University of Cluj-Napoca, Cluj-Napoca, Romania.
This article presents a tailored majority voting approach for enhancing the consistency and reliability of sentiment analysis in online product reviews. The methodology addresses discrepancies in sentiment classification by leveraging sentiment labels from multiple automated tools and implementing a robust majority decision rule. This consensus-based approach significantly enhances the trustworthiness and consistency of sentiment analysis outcomes, serving as a dependable foundation for training more precise sentiment analysis models.
View Article and Find Full Text PDFLeveraging sentiment analysis of food delivery services reviews using deep learning and word embedding.
PeerJ Comput Sci
February 2025
Department of Software Engineering, Jordan University of Science and Technology, Irbid, Jordan.
Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods online platforms is a crucial tool for learning about a company's performance. Many English-language studies have been conducted on sentiment analysis (SA).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!