빅데이터를 활용한 유치원교사와 어린이집교사에 대한 키워드 네트워크 분석: 정부조직법 개정 이후 1년을 중심으로

This study aimed to analyze and compare keyword networks related to kindergarten teachers and childcare teachers using big data collected during the year following the amendment of the Government Organization Act. Data were collected from Textom, a big data analysis platform, using the search terms “kindergarten teachers” and “childcare teachers” for the period of December 26, 2023 to December 25, 2024. After data refinement, network analysis was performed using UCINET. The findings were as follows. First, both groups shared major keywords such as “license,” “recruitment,” “education,” and “work”. Distinctive keywords also emerged: “elementary school,” “university,” and “Office of Education” for kindergarten teachers, and “subject,” “assistant,” and “practicum” for childcare teachers. Second, degree and betweenness centrality analyses showed that high-frequency keywords not only had numerous direct connections with other keywords but also played important mediating roles within each network, thereby shaping distinct societal perceptions of the two teacher groups. These findings suggest the need to integrate teacher qualifications by building on the strengths of both systems, strengthen teachers’ professionalism, and promote broader public efforts to improve recognition of early childhood teachers.