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A Big Data Analysis of Social Media Perceptions of the Korea Billiards Federation (KBF) : Focusing on Text Mining and Semantic Network Analysis

첫 페이지 보기
  • 발행기관
    국제인공지능학회(구 한국인터넷방송통신학회) 바로가기
  • 간행물
    The International Journal of Advanced Smart Convergence 바로가기
  • 통권
    Volume 14 Number 3 (2025.09)바로가기
  • 페이지
    pp.26-35
  • 저자
    Ae-Rang Kim, Keun-Ju NA, Kyung-Won Byun
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A474311

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원문정보

초록

영어
The purpose of this study is to explore public perceptions, core themes, and semantic structures surrounding the Korea Billiards Federation (KBF) using big data analysis. As the KBF transitions from a traditional recreational organization to a structured sports industry leader, it is essential to understand how the public discusses and associates the organization across digital platforms. To achieve this, data were collected from Naver, Daum, and Google between April 18, 2022, and November 30, 2024, using the keyword "Korea Billiards Federation." A total of 15,758 cases were gathered and analyzed through the Textom platform. After preprocessing the text, keyword extraction was performed based on Term Frequency (TF) and Term Frequency-Inverse Document Frequency(TF-IDF). Subsequently, a semantic network analysis was conducted using UCINET 6.0 and NetDraw to examine degree, closeness, and betweenness centrality. A CONCOR(Convergence of Iterated Correlations) analysis was also applied to classify clusters and interpret contextual meaning. As a result, four key semantic clusters emerged. First, the Division League cluster focuses on the KBF’s role in grassroots and amateur league operations. Second, the Federation cluster reflects governance, national tournaments, and referee systems. Third, the Professional cluster highlights the structure of professional leagues, rankings, and prize systems. Fourth, the Achievement cluster represents individual performance, championships, and player branding. These findings provide strategic insights into the federation’s branding, policy development, and marketing directions and serve as a foundation for the systematic development of Korea’s billiards industry.

목차

Abstract
1. Introduction
2. Research method
2.1 Data collection and analysis method
2.2. Analytical procedure
3. Results
3.1. Text mining analysis
3.2. Semantic network analysis and CONCOR analysis
4. Conclusion
Acknowledgement
References

키워드

Korea Billiards Federation (KBF) Big Data Analysis Textom platform Text Mining Semantic Network Analysis CONCOR Analysis

저자

  • Ae-Rang Kim [ Professor, Department of Sports Management, Dankook University, Korea ]
  • Keun-Ju NA [ Secretary General, Korea Billiards Federation ]
  • Kyung-Won Byun [ *Assistant Professor, Department of Graduate School of Business Administration, Dankook University, Korea ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    국제인공지능학회(구 한국인터넷방송통신학회) [The International Association for Artificial Intelligence]
  • 설립연도
    2000
  • 분야
    공학>전자/정보통신공학
  • 소개
    인터넷방송, 인터넷 TV , 방송 통신 네트워크 및 관련 분야에 대한 국내는 물론 국제적인 학술, 기술의 진흥발전에 공헌하고 지식 정보화 사회에 기여하고자 한다.

간행물

  • 간행물명
    The International Journal of Advanced Smart Convergence
  • 간기
    계간
  • pISSN
    2288-2847
  • eISSN
    2288-2855
  • 수록기간
    2012~2025
  • 십진분류
    KDC 326 DDC 380

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