스포츠 언더독 효과에 대한 빅데이터 분석

Big Data Analysis on the Underdog Effect in Sports

초록

This study aims to understand the social perception of the underdog, those who are defeated and weak in the world of sports, and the following conclusions were drawn to provide the basis of future sports underdog research. First, data collection results utilizing text mining showed that words most used in both frequency and TF-IDF were team, uprising, player, reporter and championship. Second, the results of the consolidated centrality index analysis showed the words uprising, reporter, player, team, game in said order. Third, when four clusters were formed from semantic network analysis, the first cluster was named “Sports Games”, the second “Movie”, third “Cheering” and the fourth “Marketing”.

키워드

Big data; sport; underdog; underdog effect
제목
스포츠 언더독 효과에 대한 빅데이터 분석
제목 (타언어)
Big Data Analysis on the Underdog Effect in Sports
저자
곽정현; 이선희
DOI
10.35159/kjss.2020.08.29.4.29
발행일
2020-08
저널명
한국체육과학회지
권
29
호
4
페이지
29 ~ 38

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