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학교폭력 예방을 위한 AI 상담 및 진단 테스트 통합 시스템 개발
김효림 ( Kim Hyorim ),정예원 ( Jeong Yewon ),홍은혜 ( Hong Eunhye ),김명섭 ( Kim Myeoungseob ) 한국정보처리학회 2021 한국정보처리학회 학술대회논문집 Vol.28 No.2
학교폭력 피해 사례는 꾸준히 증가하는 반면 학교폭력 예방의 대안으로 실시되고 있는 앱/웹 시스템으로는 통합성의 연계에 어려움이 있어 문제점으로 나타나고 있다. 본 논문에서 구현한 학교폭력 예방 통합 앱 시스템은 학교폭력 진단 테스트, AI 상담, 일기장, 게시판, 교화 프로그램 영상 시청 기능을 제공함으로써 이런 문제점들을 보완하였다. 또한, 진단 테스트와 상담 내용의 신뢰성을 확보하기 위해 상담 센터의 검증을 받았다. 해당 시스템의 활용을 통해 학교폭력 예방 교육의 효과를 기대할 수 있다.
김효림(Hyorim Kim),전익기(Ikki Jeon) 한국여가레크리에이션학회 2018 한국여가레크리에이션학회지 Vol.42 No.3
This study explores various keywords of the leisure activity by using big data analysis of social networks. For this purpose, web page, blogs, cafes, JISIKIN/daumTip provided by Naver and Daum were selected as analysis channels, and keywords for searching big data are leisure activity were extracted as main words. Data analysis period was limited to 4 years from january 1, 2014 to december 31, 2017. For data collection and analysis, frequency and metrics data were extracted through Textom, Social Metrics program. The degrees of the relationships were qualified by analyzing the connection structure and connection degree centrality between words by using Ucinet 6 and it’s NetDraw function. In addition, CONCOR analysis was conducted to derive clusters formed by words having similarity. The results of analysis are as follows: First, as a result of analyzing the key words through the upper words using leisure activity as a keyword, program, support, elderly, culture, insurance, time, child, family, disable, health, hobby appeared among the top 10. Second, as a result of conducting N-GRAM network graph using leisure activity as a keyword, ‘child’ and ‘insurance’ appeared the relationship between the highest word. Third, as a result of conducting cluster analysis using leisure activity as a keyword, five groups of ‘leisure welfare’, ‘leisure activity program’, ‘relieve stress’, ‘main leisure activity’, ‘sports activity’ were formed.