A Study on Golf Broadcast Recognition: Based on Big Data Analysis

This study aims to provide basic marketing data to improve viewer ratings of golf broadcasts using big data. As a research method, word frequency, TF-IDF, betweenness centrality, opinion mining, and semantic network analysis were conducted using the big data program TEXTOM and the network analysis program Ucinet6. The data collection period was a total of 6 years from January 1, 2017 to December 31, 2022. Research results: First, as a result of word frequency, TF-IDF, and betweenness centrality analysis, golf broadcasting, professional players, golf competitions, entertainment, golf king, golf channel, golf course, cast, and Jang Min-ho were extracted within the top 10. Second, the opinion mining analysis results showed positive (77.83%) and negative (22.17%) results. Third, as a result of CONCORD analysis, a total of four groups were formed: game broadcasting, entertainment, golf lessons, and general broadcasting. Accordingly, by developing the positive aspects provided by domestic golf broadcasting according to the results of this study, we hope to establish golf as a representative leisure and participation sport in Korea and serve as basic data for securing high viewership ratings for golf broadcasting.