빅데이터를 활용한 브레이킹에 대한 사회적 인식 분석

초록

The purpose of this study is to examine the public's perception of breaking through big data analysis and to present basic data on future development directions and practical tasks of breaking. The research method drew the following conclusions based on the results obtained using text mining and semantic network analysis. First, breaking, Asian Games, breaking, and Olympics appeared in the order of frequency analysis using text mining and TF-IDF analysis. Second, in the results of N-gram and connection-centeredness analysis using text mining, the words highly related to breaking appeared in the order of formula, event, adoption, sport, and battle. Third, it was composed of four clusters: game, culture, support, and education through semantic network analysis. Comprehensively, as breaking, which has conceptual differences from traditional sports, is officially recognized and promoted in international competitions, it is thought that it is necessary to encourage exchanges and cooperation between sports and cultural organizations in each country and promote the standardization and promotion of breaking worldwide. Therefore, for the continuous development of breaking, not only more attention and support in terms of the breaking game, but also more effort is needed in terms of cultural promotion, government support, and education system.

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