빅데이터를 활용한 치어리딩에 대한 사회적 인식 분석

초록

This study was conducted by using data analysis and purpose of research direction to provide the results of research direction to provide research direction and purpose of research direction for the development of supporting supporting the following results and purpose of research direction. First, the data collection results of Text mining show that the words that appear most frequently are cheerleaders, performers, competitions, organizers, dancers, teams, hosts, cheerleaders, members, and associations. Second, the words with the highest TF-IDF weight of the words related to cheerleaders mined from the Text mining are performance, cheerleaders, competitions, members, Incheon, Michuhol District, dance, opening, team and teenagers. Thirdly, in the N-gram analysis using Text mining, the words with high correlation with cheerleaders are competition, performance, association, children, and association in turn. Fourth, the connection centrality of the words related to cheerleaders excavated from Text mining is Incheon, Michuhol District, cheerleaders association, founding ceremony, team, competition, association, performance, hosting, and challenge. Fifthly, through semantic connectivity network analysis, it can be seen that there are four population clusters: the first cluster is named sports, the second cluster is named associations, the third cluster is named objects, and the fourth cluster is named culture.

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