A study on the Success of Sports Animation using Social Big data analysis: Focusing on the Slam Dunk Syndrome

Abstract

This study aims to analyze keywords, emotions, and perceptions of sports animation through social big data analysis. As a research method, text mining, opinion mining, and semantic network analysis were conducted using Textome, a social matrix big data platform. The research results are as follows. First, as a result of word frequency, TF-IDF, and connection centrality analysis, the keywords first, slam dunk, movie, Japan, release, comic book, animation, sales, box office, and audience all appeared in the top 10, confirming that they are key keywords. Second, as a result of opinion mining analysis, positive words (76.38%) appeared and negative words (23.61%), indicating that there are many positive keywords. Third, as a result of the CONCOR analysis, two groups were formed: ‘sports animation contents’ and ‘sports animation products’.