학술논문
키워드 네트워크 분석을 통한 청소년 사이버도박 관련 온라인 기사의 특성 분석
An Analysis of Characteristics of Online Articles Related to Youth Cyber Gambling through Keyword Network Analysis
An Analysis of Characteristics of Online Articles Related to Youth Cyber Gambling through Keyword Network Analysis
Document Type
Article
Author
Source
미래청소년학회지 / Journal of Future Oriented Youth Society. Mar 31, 2024 21(1):123
Subject
Language
Korean
English
English
ISSN
1738-4753
Abstract
본 연구의 목적은 키워드 네트워크 분석을 통하여 청소년 사이버도박과 관련된 온라인 기사의 특성을 파악하고 향후 청소년 사이버도박 예방 및 개입을 위한 시사점을 제공하는 것이다. 이를 위해 2015년 1월 1일부터 2023년 12월 31일까지 온라인에 보도된 청소년 사이버도박 관련 기사 1,830건을 대상으로 하여 주요 키워드의 빈도분석과 네트워크 분석을 실시하였다. 본 연구의 결과는 다음과 같다. 첫째, 주요 키워드는 게임, 불법, 중독, 사이트, 예방, 범죄, 교육 등의 순으로 나타났다. 둘째, 주요 키워드에 대한 동시출현빈도는 ‘관리-센터’, ‘한국-센터’, ‘한국-관리’, ‘예방-교육’, ‘조사-결과’, ‘중독-예방’ 등의 순으로 +나타났다. 셋째, 연결중심성이 가장 높은 키워드는 ‘불법’, ‘중독’, ‘이용’, ‘운영’, ‘한국’, ‘인터넷’, ‘학교’, ‘경찰’, ‘범죄’ 등이었다. TF-IDF에서 ‘불법’이 특정 문서에서 중요도가 가장 높게 나타났으며, ‘게임’, ‘중독’, ‘예방’, ‘사이트’, ‘교육’, ‘범죄’, ‘경찰’, ‘인터넷’, ‘학교’ 등이 뒤를 이었다. 넷째, CONCOR분석에서 4개의 군집으로 분류되었으며, ‘위험한 사이버도박의 증가’, ‘사이버도박 예방 및 개입’, ‘사이버도박의 규제’, ‘사이버도박의 법적 처벌’로 군집명을 정하였다. 본 연구의 분석결과를 토대로 청소년 사이버도박을 예방할 수 있는 다각적인 방안을 제시하였다.
The purpose of this study is to identify the characteristics of online articles related to youth cyber gambling through keyword network analysis and provide implications for future prevention and intervention strategies for youth cyber gambling. To this end, the frequency analysis and network analysis of major keywords were conducted on 1,830 online articles related to youth cyber gambling in online articles from January 1, 2015 to December 31, 2023. The results of the analysis are as follows. First, the major keywords were identified in the order of ‘game,’ ‘illegal,’ ‘addiction,’ ‘site,’ ‘prevention,’ ‘crime,’ and ‘education,’ and so on. Second, in terms of co-occurrence frequency, the major keyword pairs were ranked in the order of ‘management-center,’ ‘Korea-center,’ ‘Korea-management,’ ‘prevention-education,’ ‘investigation-results,’ ‘addiction-prevention,’ and so on. Third, the keywords with the highest degree of centrality included ‘illegal,’ ‘addiction,’ ‘utilization,’ ‘operation,’ ‘Korea,’ ‘internet,’ ‘school,’ ‘police,’ ‘crime,’ and so on. In TF-IDF, ‘illegal’ showed the highest significance in specific documents, followed by ‘game,’ ‘addiction,’ ‘prevention,’ ‘site,’ ‘education,’ ‘crime,’ ‘police,’ ‘internet,’ ‘school,’ and so on.” Fourth, through CONCOR analysis, the data were classified into the four clusters, which were categorized as ‘Rising Concerns of Cyber Gambling,’ ‘Prevention and Intervention for Cyber Gambling,’ ‘Regulation of Cyber Gambling,’ and ‘Legal Penalties for Cyber Gambling.’ Based on the analysis results, various approaches to prevent youth cyber gambling were proposed.
The purpose of this study is to identify the characteristics of online articles related to youth cyber gambling through keyword network analysis and provide implications for future prevention and intervention strategies for youth cyber gambling. To this end, the frequency analysis and network analysis of major keywords were conducted on 1,830 online articles related to youth cyber gambling in online articles from January 1, 2015 to December 31, 2023. The results of the analysis are as follows. First, the major keywords were identified in the order of ‘game,’ ‘illegal,’ ‘addiction,’ ‘site,’ ‘prevention,’ ‘crime,’ and ‘education,’ and so on. Second, in terms of co-occurrence frequency, the major keyword pairs were ranked in the order of ‘management-center,’ ‘Korea-center,’ ‘Korea-management,’ ‘prevention-education,’ ‘investigation-results,’ ‘addiction-prevention,’ and so on. Third, the keywords with the highest degree of centrality included ‘illegal,’ ‘addiction,’ ‘utilization,’ ‘operation,’ ‘Korea,’ ‘internet,’ ‘school,’ ‘police,’ ‘crime,’ and so on. In TF-IDF, ‘illegal’ showed the highest significance in specific documents, followed by ‘game,’ ‘addiction,’ ‘prevention,’ ‘site,’ ‘education,’ ‘crime,’ ‘police,’ ‘internet,’ ‘school,’ and so on.” Fourth, through CONCOR analysis, the data were classified into the four clusters, which were categorized as ‘Rising Concerns of Cyber Gambling,’ ‘Prevention and Intervention for Cyber Gambling,’ ‘Regulation of Cyber Gambling,’ and ‘Legal Penalties for Cyber Gambling.’ Based on the analysis results, various approaches to prevent youth cyber gambling were proposed.