뉴스 빅데이터를 활용한 지방소멸위기 대응 평생교육 토픽 분석

초록

This study aims to explore the structure and meaning of major discourses on lifelong education related to the response to the local extinction crisis, as reflected in domestic media reports over the past 10 years (2016–2025), utilizing the news big data analysis system, BigKinds. To achieve this, keyword frequency analysis and Latent Dirichlet Allocation (LDA) topic modeling were conducted on a total of 553 news articles using TEXTOM. First, the frequency analysis identified 'university,' 'education,' 'lifelong learning city,' 'future,' and 'assembly' as core keywords. Second, the topic modeling analysis derived nine major topics, among which ‘the expansion of the university's role for regional economic revitalization and the attraction of foreigners’ accounted for the highest proportion. Synthesizing the findings, the discourse on lifelong education response in the era of the local extinction crisis can be discussed from four perspectives: ‘the strengthening of the university-centered lifelong education frame’, ‘the emergence of multi-layered governance and resident autonomy discourse’, ‘the imbalance of discourse on youth settlement and living/cultural infrastructure’, and ‘a consideration of the policy instrumentalization of lifelong education and its new social purposes.’ This study examines the social role of lifelong education amidst the local extinction crisis and provides implications for establishing future policy directions and strategies.

키워드