빅데이터를 활용한 중국태권도 현황 및 인식 분석

Abstract

This study uses big data to analyze the public's cognition and attention to Chinese Taekwondo after the reform of the Chinese Taekwondo Association, and provides necessary basic data for the formulation of future development policies for Chinese Taekwondo. Through text mining and semantic network analysis, the following conclusions are obtained: First, the most frequently occurring words are Taekwondo, Chinese team, Asian Games, member, gold medal, technology, champion, youth, Olympic Games, and athlete. The words with the highest TF-IDF weight are Taekwondo, Asian Games, Olympic Games, member, gold medal, technology, youth, champion, Taekwondo Hall, and college student. Second, through N-gram analysis, it is found that the words highly related to Taekwondo are ranked by frequency as champion, world, public, Asian Games, and member. Third, through semantic network analysis, it can be seen that it consists of four clusters, named sports, association, education, and public