Keyword Network Analysis through Big Data on Well-being of Young Children with Disabilities

• 발행기관: The Pacific Early Childhood Education Research Association(환태평양유아교육연구학회)
• 저자명: Hyung Mee Kim
• 간행물 정보: 『Asia-Pacific journal of research in early childhood education』Vol.18 No.1, 55~79쪽, 전체 25쪽
• 주제분류: 사회과학 > 교육학
• 파일형태: PDF
• 발행일자: 2024.01.01

국문 초록

This study was to examine the overall perception of Korean society on well-being of young children with disabilities in big data. For this purpose, Textom, a big data analysis solution, was used to collect data during each period of the 3rd-5th Comprehensive Policy Plan for People with Disabilities, using ‘young children with disabilities + well-being’ as keywords. On the collected raw data, data cleaning was conducted as primary and secondary refinement procedures to select the top 200 keywords, which were then subjected to network analysis. After conducting a network analysis targeting the top 200 keywords, the main results are as follows. First, as a result of the keyword frequency analysis, 'health' and ‘education’ ranked highly across the 3rd, 4th, 5th plans, which can be interpreted as indicating that ‘health’ and ‘education’ are most often mentioned in social discussions about the well-being of young children with disabilities. Second, examining the relationship between keyword networks on the well-being of young children with disabilities by the plans, the degree centrality analysis revealed that well-being of young children with disabilities was recognized socially in a physical aspect, but moved towards a comprehensive concept that that includes various aspects. In both the closeness and betweenness centrality analyses, ‘health’ was found to be high in all three plans. Based on these results, it is important to understand the social perception of well-being of young children with disabilities and to provide a basis for research, policy, and national support for young children with disabilities.

목차

Introduction

Method

Results

Discussion

키워드

children with disabilities well-being big data network analysis