메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
최수정 (숙명여자대학교) 이상일 (숙명여자대학교)
저널정보
한국체육과학회 한국체육과학회지 한국체육과학회지 제28권 제5호 (인문사회과학 편)
발행연도
2019.10
수록면
441 - 462 (22page)
DOI
10.35159/kjss.2019.10.28.5.441

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

이 논문의 연구 히스토리 (2)

초록· 키워드

오류제보하기
The purpose of this study was to find the current spectators’ perception of Korean Basketball League(KBL) through big data analysis, and to find development plans for KBL based on that.
For this purpose, the data was collected from Naver Blog and Naver Cafe by using Textom software with the key words(professional basketball, KBL). In data mining analysis, the key words related to KBL was drawn through frequency analysis and TF-IDF. In addition, in semantic network analysis, the relations between key words and sentiments were visualized through key words-sentiment network analysis.
The results from the above study methods are as follows. First, the quantity of the buzz collected from the preparation period was much less than the quantity of the buss collected from the season period. Second, the results of data mining analysis showed different patterns in preparation period and season period, and the season and the whole period showed a similar pattern. Third, in the semantic network analysis, it was found that neutral emotion is highly correlated with athlete, and referee. Positive emotion is highly correlated with salary, athlete, Seo, Jang-hun, and negative emotion is derived form referee and Jung-hyun Lee.
Based on the above results, this study suggests development of star players, utilization of retired players, utilization of media, and expansion of social contribution activities. Also, it proposes changing the referee system, the establishment of the video assistant referee system and the formation of the fan committee.

목차

Abstract
Ⅰ. 서론
Ⅱ. 연구방법
Ⅲ. 결과
Ⅳ. 논의
Ⅴ. 결론 및 제언
참고문헌

참고문헌 (79)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

이 논문과 함께 이용한 논문

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2019-692-001319707