Big Data–Driven Analysis of Media Coverage on Issues Surrounding Sports Violence
Purpose: This study employed a big data approach to analyze news articles related to sports violence, with the aim of identifying prevailing trends and characteristics in Korean society over the past decade.<br/> Method: This study utilized the BIG Kinds database to collect and analyze news articles related to sports violence in order to identify major keywords and emerging issues. A total of 4,700 articles were retrieved using the keyword “sports violence” from July 1, 2015, to June 30, 2025. For the analysis, Python’s scikit- learn package was employed to perform word frequency, TF-IDF, network, and CONCOR analyses.<br/> Results: First, athletes and coaches were identified as the primary agents of sports violence, with violence and human rights emerging as central issues. Moreover, the active involvement of the Korea Sports Council, the National Human Rights Commission of Korea, and the Ministry of Culture, Sports and Tourism suggests that sports violence is increasingly recognized not merely as individual deviance but as a systemic and structural problem. Second, the CONCOR analysis revealed eight distinct clusters: (a) incidents of sports violence and human rights investigations; (b) prevention and education regarding violence in school athletic teams; (c) disciplinary measures and reforms in sports governance; (d) female victims within the sports sector; (e) violent speech and behavior exhibited by coaches; (f) the eradication of sexual violence and corruption in sports alongside institutional reform; (g) the establishment of systems for sports ethics and human rights protection; and (h) controversies surrounding school violence in professional volleyball.<br/> Conclusion: This study serves as a valuable resource for shaping policies, preventive measures, and practical guidelines to address human rights violations in sports.
Authors
- Sujin Kim (ORCID: https://orcid.org/0000-0002-7878-4322)
- Geumran Seo
Publication Details
- Journal
- Journal of Sport and Leisure Studies
- Published
- 2025-10-31
- DOI
- https://doi.org/10.51979/kssls.2025.10.102.431
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00