지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.7
- 수록면
- 53 - 61 (9page)
- DOI
- 10.51979/KSSLS.2020.07.81.53
이용수
초록· 키워드
오류제보하기
Purpose: In this study, using the INSIGHT Deep MiningG program, frequency of mentioning and Emotion-Keyword are compared on a percentage basis to analyze the effect of a derived market of demand-oriented market value network classification on the creation of sports-related jobs.
Method: Based on the preceding factors derived from social data analysis, the following conclusions were reached by using the method, partial least-square (PLS), to determine what influence derivative market has on the critical attributes of job creation. The study used the INSIGHT Deep MiningG program to analyze the impact of derived markets on the creation of sports-related jobs by using the demand-oriented market value chain classification as a percentage of social data references and emotional keywords. The following conclusions were reached using the PLS (PLS) regression method to determine the impact of job creation.
Results: The results of this study are as follows. First, social users had the highest interest in the sports information market and the sports service market, given the amount of mention in the sports derivatives market of social data. Regarding sports job factors, interest in recruiting and job information was high. Second, the Emotion-Keyword of the sports derivative market showed high positive sentiment corresponding to the image of the new growth industry, while the Emotion-Keyword of the sports job showed negative sentiment due to the anxiety caused by issues such as unfair recruitments. Third, derivative market in the market value network mostly affected sports jobs.
Conclusion: Job seekers prefer to work in the sports information market, sports service market, sports athlete training market, and sports tourism market, but the actual employment status is reflected in the sports information market, sports service market, sports tourism market, and sports facility market.
Method: Based on the preceding factors derived from social data analysis, the following conclusions were reached by using the method, partial least-square (PLS), to determine what influence derivative market has on the critical attributes of job creation. The study used the INSIGHT Deep MiningG program to analyze the impact of derived markets on the creation of sports-related jobs by using the demand-oriented market value chain classification as a percentage of social data references and emotional keywords. The following conclusions were reached using the PLS (PLS) regression method to determine the impact of job creation.
Results: The results of this study are as follows. First, social users had the highest interest in the sports information market and the sports service market, given the amount of mention in the sports derivatives market of social data. Regarding sports job factors, interest in recruiting and job information was high. Second, the Emotion-Keyword of the sports derivative market showed high positive sentiment corresponding to the image of the new growth industry, while the Emotion-Keyword of the sports job showed negative sentiment due to the anxiety caused by issues such as unfair recruitments. Third, derivative market in the market value network mostly affected sports jobs.
Conclusion: Job seekers prefer to work in the sports information market, sports service market, sports athlete training market, and sports tourism market, but the actual employment status is reflected in the sports information market, sports service market, sports tourism market, and sports facility market.
목차
Ⅰ. 서론
Ⅱ. 연구방법
Ⅲ. 결과
Ⅳ. 논의
Ⅴ. 결론 및 제언
참고문헌
ABSTRACT
참고문헌 (22)
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