빅데이터를 활용한 노인 주거 뉴스 기사 분석

Big Data Analysis on News Articles about Elderly Housing

Background/Objectives: As Korea enters an aged society, housing issues for the elderly have become a significant social concern. The housing stability of older adults is closely linked to their health, social relationships, and quality of life, making it a critical condition for a dignified old age. This study aims to analyze news articles related to elderly housing, identifying main key keywords and their connections to establish the fundamental issues surrounding elderly housing. Methods: This study was conducted using big data analysis techniques based on news article data. A total of 1,324 news articles related to elderly housing, collected from 1990 to 2024, were used for analysis. In the final analysis, a total of 6,993 words were utilized. Term frequency and term frequency-inverse document frequency analyses were conducted, and co-occurrence network analysis was performed using VOSviewer. Results: The analysis revealed that keywords such as “elderly”, “65 years old”, “silver town”, “Ministry of Land, Infrastructure and Transport”, and “Korea Land and Housing Corporation” showed high frequency and importance. The co-occurrence network analysis identified five key topics related to elderly housing: senior-specific housing and welfare services, housing welfare and rental housing policies, elderly welfare policies from the Ministry of Health and Welfare, silver town revitalization policies, and community-based integrated care policies. These findings highlight that most discussions focus on major policies and systems related to elderly housing, with government and local authorities playing a central role. Conclusion/Implications: Elderly housing requires integrated support beyond just providing living spaces. Active collaboration between the government, private sector, and local communities is essential. Future policies should focus on customized housing models and community-based services, while preventing social isolation.