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The purpose of this study is to explore the use of FGC in the gaming industry. More specifically, this study investigated two research objectives: (1) to examine key hidden topics from FGC, and (2) to investigate the effects of the COVID-19 pandemic on message structure of FGC. We collected data from the game companies¡¯ official Twitter account, resulting in 58,386 tweets. We used Python scripts and Twitter API. In order to investigate our research objectives, we used text mining analytics and topic modeling. We found eight latent topics in FGC, including update, online, and series. Moreover, we found differences related to term frequence betweeen before and after COVID-19. Based on findings, our study contributes to the overwhelmingly exploratory literature on research addressing social media marketing by examining the use of FGC by following the empirical approaches of data mining.