코로나19 확산에 따른 태권도 분야 이슈 분석
An Analysis of Issues in the Field of Taekwondo Caused by the Spread of COVID-19
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이 연구의 목적은 뉴스 기사를 바탕으로 토픽 모델링 분석을 하여 코로나19 사태 이후 언론과 대중들에게 주요 관심사로 떠오른 태권도 관련 이슈를 분석하는 것이다. 분석을 위해 빅카인즈에서 ‘코로나’와 ‘태권도’ 관련 뉴스 기사를 수집하였고 수집된 뉴스 기사는 넷마이너(netminer 4)를 사용하여 텍스트 데이터 중 한글 명사만 추출하였다. 추출한 데이터는 정제 과정을 거쳐 TF-IDF 계수가 0.4 이하로 나타난 ‘신종’, ‘바이러스’, ‘코로나’ 단어를 제거하였다. 이후 LDA(latent dirichlet allocation) 토픽 모델링 분석을 실시하여 토픽을 도출하였다. 도출된 토픽은 확률분포가 높은 단어 10개를 중심으로 원문을 검토하여 토픽명을 명명하였으며, 총 5개의 토픽이 도출되었다. 그리하여 각 토픽에 해당되는 문서의 비중을 산출하여 비중이 높은 순서대로 제시하였다. 첫 번째 토픽에 나타난 ‘취소(.032)’, ‘행사(.030)’, ‘감염증(.026)’, ‘지역(.024)’, ‘연기(.022)’, ‘체육(.022)’, ‘여파(.018)’, ‘체육계(.016)’, ‘대회(.015)’, ‘예정(.014)’ 단어를 참고하여 토픽명을 ‘태권도 행사 취소’로 명명하였다. 두 번째 토픽에 나타난 ‘학원(.027)’, ‘서울(.019)’, ‘관광(.017)’, ‘학교(.016)’, ‘태권도(.015)’, ‘경기관광공사(.015)’, ‘시군(.014)’, ‘초등학교(.013)’, ‘경기도(.011)’, ‘코로나 키즈(.011)’ 단어를 참고하여 토픽명을 ‘코로나 속 일상 변화’로 명명하였다. 세 번째 토픽에 나타난 ‘태권도(.064)’, ‘태권도협회(.031)’, ‘어려움(.023)’, ‘지역(.017)’, ‘회원(.017)’, ‘대전(.017)’, ‘지원(.015)’, ‘전달(.015)’, ‘기부(.012)’, ‘옥천군(.012)’ 단어를 참고하여 토픽명을 ‘코로나 극복 노력’으로 명명하였다. 네 번째 토픽에 나타난 ‘올림픽(.055)’, ‘선수(.028)’, ‘도쿄올림픽(.028)’, ‘대표(.025)’, ‘국제(.019)’, ‘국가(.019)’, ‘선수촌(.018)’, ‘위원회(.016)’, ‘진천(.016)’, ‘개최(.015)’ 단어를 참고하여 토픽명을 ‘도쿄올림픽 개최 여부’로 명명하였다. 다섯 번째 토픽에 나타난 ‘문화(.032)’, ‘정부(.015)’, ‘콘텐츠(.014)’, ‘진행(.014)’, ‘개학(.014)’, ‘감염증(.012)’, ‘화상(.011)’, ‘장관(.011)’, ‘재단(.011)’, ‘학생(.011)’ 단어를 참고하여 토픽명을 ‘온라인 활용과 확산’으로 명명하였다.
Abstract
The purpose of this study is to make an analysis of issues related to Taekwondo that have recently become the main interest amongst media and the general public after the COVID-19(coronavirus Disease-19 outbreak by carrying out topic modeling analysis based on the news articles. For analysis, Subjects of analysis include 91 news articles that are searched with keywords of ‘corona’ and ‘Taekwondo’ from the BIG KINDS. From the news articles collected, this study extracted only Korean nouns out of text data using NetMiner 4. Extracted data went through a filtering process. After that, this study removed words such as ‘new’, ‘virus’ , and ‘corona’ that TF-IDF (term frequency-inverse document frequency) was shown as less than 0.4. Following the foregoing, this study deduced topics by carrying out LDA (Latent Dirichlet Allocation) topic modeling analysis. For deduced topics, this study designated topic titles by examining original text focusing on 10 words with a high probability distribution. As a result of topic modeling, 5 topics have been produced. This study calculated the relative importance of documents equivalent to each topic and suggested in order of documents with higher importance. This study referred to the words like ‘cancelled’, ‘event’, ‘infectious disease’, ‘area’, ‘delayed’, ‘sports’, ‘aftermath’, ‘sports world’, ‘competition’, ‘scheduled’ which were shown in the first topic, and designated topic title as ‘cancellation of Taekwondo event’. Referring to the words such as ‘private institute’, ‘Seoul’, ‘tour’, ‘school’, ‘Taekwondo’, ‘Gyeonggi Tourism Organization’, ‘city and county’, ‘elementary school’, ‘Gyeonggi-do’, ‘corona kids’ shown in the second topic, this study named topic title as ‘daily changes in corona’. For the words shown in the third topic such as ‘Taekwondo’, ‘Taekwondo Association’, ‘hardship’, ‘area’, ‘member’, ‘Daejeon’, ‘support’, ‘deliver’, ‘donation’ and ‘Okcheon-gun’, this study named topic title ‘efforts to overcome corona’. For ‘Olympic’, ‘player’, ‘Tokyo Olympics’, ‘representative’, ‘international’, ‘state’, ‘Olympic village’, ‘committee’, ‘Jincheon’ and ‘holding’ shown in the fourth topic, this study gave a name of ‘possibility of holding Tokyo Olympics’ to the topic title. And for the words such as ‘culture’, ‘government’, ‘contents’, ‘progress’, ‘the begging of school’, ‘infectious disease’, ‘video’, ‘minister’, ‘foundation’, ‘student’ shown in the fifth topic, this study named topic title ‘use and spread of online’.
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