뉴스 빅데이터를 활용한 저출산 및 출산율의 키워드 트렌드 분석

Analyzing Keyword Trends in Fertility and Low Birth Rates Using News Big Data

Objective: The current study aims to analyze discussions on fertility and birthrate in news big data in order to address the severe and prolonged decline in birthrate. Methods: We analyzed economy/society news from 2006 to present, focusing on ‘declining birthrate’ and ‘fertility rate.’ Our approach combined relevant word and trend analysis, using a Structured Support Vector Machine algorithm for the top 100 news reports to map keyword connections, and assessing keyword frequency and correlation over time. Additionally, we used the Topic Rank algorithm for a TF-IDF based word cloud, highlighting co-occurring word frequencies. Results: It is notable that ‘employment’ and ‘parental leave’ were highly associated with ‘low birthrate’ and ‘fertility rate’ highlighting their direct link to workplace and economic activities. Concerns about job stability and career disruption, especially regarding parental leave and post-childbirth work return are key in understanding their correlations. The Second Basic Plan emphasizes harmonizing work and family life, advocating for improve childcare leave systems and flexible work arrangements. Conclusions: From a policy demand perspective, meaningful change in fertility rates can be achieved by ensuring job security and a corporate culture and social environment in which parental leave is available.