스포츠 언더독 효과에 대한 빅데이터 분석

Abstract

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”.