빅데이터 분석 기반 한류 현상 이해와 한국어교육에의 응용

Abstract

This study investigates the structural changes in Korean Wave (Hallyu) discourse by analyzing English-language big data collected from Google platforms, including news articles, web documents, and social media content. By dividing the big data into two distinct periods—before and during the COVID-19 pandemic—and employing text mining analysis, the study identifies salient keywords related to Hallyu and maps their respective semantic network structures. Findings indicate that Hallyu discourse has noticeably shifted from a primary focus on K-pop performance content and participatory fandom culture toward a new emphasis on platform-based consumption, language learning, and institutional engagement. Hence, this research highlights how Hallyu has evolved into a complex discourse system, prompting a significant need to move beyond K-pop-centered approaches and integrate theme-based, contextually informed content design into Korean language education. However, limitations of this study include its exclusive reliance on English-language data and a primary emphasis on quantitative analysis. Future research should expand to include multilingual corpora, incorporate topic modeling, and employ qualitative discourse analysis to further enrich pedagogical applications.