인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2026.1
- 수록면
- 205 - 218 (14page)
- DOI
- 10.51979/KSSLS.2026.01.103.205
이용수
초록· 키워드
Purpose: The purpose of this study is to explore how the meanings associated with women’s participation in sports have evolved within Korea by analyzing media coverage from 1995 to 2024.
Method: A Python-based Jupyter Notebook environment was used for data preprocessing and analysis. News articles related to women’s sports were collected from the BigKinds database over a 30-year period, from January 1, 1995, to December 31, 2024. Word frequency analysis, term frequency–inverse document frequency (TF–IDF) analysis, network analysis, and CONCOR analysis were conducted using scikit-learn and other relevant Python packages. The final dataset consisted of 39,908 articles from 1995–2004, 54,176 articles from 2005–2014, and 81,270 articles from 2015–2024.
Results: First, analysis of keyword frequencies revealed that terms such as match, athlete, Korea, victory, record, Olympics, golf, and gold medal were dominant throughout the study period. These findings suggest that media coverage of women’s sports has been largely shaped by themes of competition, performance outcomes, and medal achievements, reflecting a win-oriented perspective and a strong emphasis on elite sport. Second, CONCOR analysis identified a total of 18 clusters, with five clusters in Period 1 (1995–2004), six clusters in Period 2 (2005–2014), and seven clusters in Period 3 (2015–2024), indicating increasing thematic diversification over time.
Conclusion: This study highlights the characteristics of social discourse surrounding women’s sports in Korean media and emphasizes the need to incorporate more multidimensional perspectives to support the sustainable development of women’s sports.
Method: A Python-based Jupyter Notebook environment was used for data preprocessing and analysis. News articles related to women’s sports were collected from the BigKinds database over a 30-year period, from January 1, 1995, to December 31, 2024. Word frequency analysis, term frequency–inverse document frequency (TF–IDF) analysis, network analysis, and CONCOR analysis were conducted using scikit-learn and other relevant Python packages. The final dataset consisted of 39,908 articles from 1995–2004, 54,176 articles from 2005–2014, and 81,270 articles from 2015–2024.
Results: First, analysis of keyword frequencies revealed that terms such as match, athlete, Korea, victory, record, Olympics, golf, and gold medal were dominant throughout the study period. These findings suggest that media coverage of women’s sports has been largely shaped by themes of competition, performance outcomes, and medal achievements, reflecting a win-oriented perspective and a strong emphasis on elite sport. Second, CONCOR analysis identified a total of 18 clusters, with five clusters in Period 1 (1995–2004), six clusters in Period 2 (2005–2014), and seven clusters in Period 3 (2015–2024), indicating increasing thematic diversification over time.
Conclusion: This study highlights the characteristics of social discourse surrounding women’s sports in Korean media and emphasizes the need to incorporate more multidimensional perspectives to support the sustainable development of women’s sports.
#Korea women’s sports
#Social perception
#Text mining
#Big data analytics
#Changes in women’s sports
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목차
- Ⅰ. 서론
- Ⅱ. 연구방법
- Ⅲ. 결과
- Ⅳ. 논의
- Ⅴ. 결론 및 제언
- 참고문헌
- ABSTRACT
참고문헌
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