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The purpose of this study is to find out the social discourse of ECEC integration using big data. Big data related to ECEC integration from 2013 to 2023 were collected using Textorm. The collected raw data were refined, and among them 50 keywords were selected as a result of frequency analysis. The results of the study are as follows. First, the social discourse of ECEC integration showed high frequency in the order of ‘teacher’, ‘child care center’, ’kindergarten’, ‘child care’, and ‘qualification’. As a result of cluster analysis, social discourse was formed centering on three core discourses such as teacher qualification acquisition, policy direction, and consultation subject. Second, major keywords such as ‘child care center’, and ‘kindergarten’ have a higher degree of centrality, while word such as ‘policy’, and ‘Korea National Open University’ have a higher closeness centrality. Third, the ego network analysis was conducted on the main keywords with higher centrality and frequency, such as ‘teacher’ and ‘qualification’. In addition, the ego network analysis was performed and visualized the main keywords and visualized. Through this study, the social discourse was investigated and implications for approach of ECEC integration were discussed.
Han et al. (Sun,) studied this question.