대학수학능력시험 영어영역에 대한 사회적 담론 분석: 자연어 처리 기반 텍스트 마이닝과 소셜 네트워크 분석을 활용한 2021-2024년 온라인 미디어 분석

• 영문명: A social discourse analysis on the English section of the Korean college scholastic ability test: Analysis of online media from 2021 to 2024 using natural language processing-based text mining and social network analysis
• 발행기관: 한국영어교과교육학회
• 저자명: 최현용(Whyun Young Choi)
• 간행물 정보: 『영어교과교육』24권 1호, 151~177쪽, 전체 27쪽
• 주제분류: 사회과학 > 교육학
• 파일형태: PDF
• 발행일자: 2025.02.28

국문 초록

This study analyzes social discourse on the English section of the Korean College Scholastic Ability Test (K-CSAT) in online media from 2021 to 2024, using Natural Language Processing (NLP)-based text mining and Social Network Analysis (SNA). Scrutiny of 88,561 online documents employed Term Frequency (TF), Term Frequency-Inverse Document Frequency (TF-IDF), Bigram, CONvergence of iteration CORrelation (CONCOR), and sentiment analysis. The findings reveal three distinctive patterns. First, despite the introduction of absolute evaluation in 2018, grade-centered hierarchical culture remains dominant, leading to increased dependence on private education, as evidenced by ‘cram school (or private institute)’ showing the highest importance in TF-IDF analysis and eight differentiated learning strategy clusters emerging in CONCOR analysis. Second, early preparation trends are prominent, with the high importance of the ‘middle school’ keyword indicating that K-CSAT preparation begins at the middle school level. Third, sentiment analysis reveals that while positive sentiment (67.11%) predominates, negative sentiment (32.89%) is also significant, with learning burden and psychological pressure as major concerns. This study provides empirical data for policy improvement through comprehensive analysis of social perceptions regarding the K-CSAT English section.

목차

I. 서론

II. 연구 방법

III. 연구 결과

IV. 논의 및 함의

V. 결론

참고문헌

키워드

사회적 담론 분석 대학수학능력시험 텍스트 마이닝 소셜 네트워크 분석 social discourse analysis Korean college scholastic ability test text mining social network analysis