Paper Title
SOCIAL BIG DATA ANALYSIS TO EXPLORE HALLYU FIELDS

Abstract
Abstract - The purpose of this study is to explore the new fields of Hallyu by identifying major keywords and topics latent in big data. Specifically, this study conducts text mining to identify changes in perceptions and issues about the Hallyu fan, which is increasing in the recently emerging K-cultural content industry. Therefore, unstructured text data reported from January 1, 2018 to November 30, 2022 in the social channel were collected, refined, analyzed, and visualized using the Textom solution. Text mining and topic modeling analysis were performed by extracting 40,145 keywords in 2018, 39,800 keywords in 2019, 30,057 keywords in 2020, 32,985 keywords in 2021, and 33,398 keywords in 2022 from a total of 78,173 data. Findings showed that three topics were derived in 2018, four topics in 2019, four topics in 2020, four topics in 2021, and five topics in 2022, and topic names were assigned to each topic. As a result of categorizing these, nine themes were derived: K-music, K-film, K-fan countries, K-fashion, K-sports, K-tourism, K-publishing, K-economy, and K-stars. Findings are meaningful in that the resultant topics can be used as basic data for in-depth research on Hallyu studies by identifying changes in public perception and issues regarding Hallyu fan. Keywords - Hallyu, Fandom, K-pop, Social Big-data, Topic Modeling, Text Mining.