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.
피인용 0
초록·키워드
This study aims to empirically analyze public perceptions and discourse patterns surrounding the issue of ticket scalping in Korean professional baseball, and to propose policy-oriented responses based on the findings. To this end, text mining techniques were applied to relevant web documents collected from major Korean portal sites (Naver, Daum) between December 2024 and March 2025. The analysis included keyword frequency analysis, degree centrality analysis, semantic network analysis, and CONCOR cluster analysis. The results show that keywords such as ‘professional baseball’ (3,693), ‘scalping’ (1,558), ‘transaction’ (1,355), ‘purchase’ (527), ‘illegal’ (514), ‘price’ (511), ‘report’ (411), ‘law’ (304), and ‘macro’ (294) had both high frequency and centrality. This indicates that scalping is not merely perceived as a transactional issue but as a legal and social problem that requires institutional response. Co-occurrence network analysis further revealed that keyword pairs such as ‘calping/transaction,’ ‘ticket/reservation,’ ‘scalping/report,’ ‘illegal/transaction,’ and ‘investigation/request’ were central to the network, suggesting that public discourse on scalping is largely negative and focused on enforcement and regulation. In addition, CONCOR cluster analysis categorized the keywords into six thematic groups: ‘game attendance,’ ‘purchase methods,’ ‘transaction methods,’ ‘games,’ ‘prevention,’ and ‘illegality.’
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-151-26-02-096317541
