Decoding Kindergarten Management Policies: A Python - Based Big Data Text Analysis Across China, Japan, and Sweden

China's growing focus on early childhood education spurs this research. Leveraging big data text analysis with Python, This study examines China's current regulations through a comparative lens, integrating experiences from international case studies. We gathered 34 kindergarten management policies from China, Japan, and Sweden. Employing big-data-driven word frequency stats, we spotlight key policy terms, visualizing them as word clouds. A Latent Dirichlet Allocation (LDA) topic model, applied to large-scale datasets, identifies distinct policy-making priorities across nations. The findings indicate three key patterns: (1) Japan prioritizes policy implementation efficiency and safety compliance; (2) Sweden adopts mandatory government-led regulations to standardize early childhood services; (3) China emphasizes teacher-child rapport and a care-education integrated model in kindergarten management, yet lags in establishing systematic evaluation frameworks compared to international counterparts. This study advocates for the development of a distinctively Chinese kindergarten management model grounded in teacher-child relationships, while systematically incorporating international best practices in early childhood education governance to catalyze high-quality pedagogical advancement.