텍스트 마이닝을 이용한 ‘다문화’ 신문 기사 분석

Abstract

Over the past few decades, Korean society has experienced a transition towards multiculturalism through rapid demographic changes and economic development. These shifts have significantly impacted government policies, social discourse, and public perceptions, providing an essential backdrop for understanding the evolution of multicultural policies and changes in social acceptance. This study aims to analyze the changes in South Korea's multicultural policies and social perceptions from 2008 to 2024 using text mining techniques on newspaper articles. The research utilizes the BIGKinds database from the Korea Press Foundation to collect articles related to multiculturalism published in major daily newspapers from 2008 to 2024. The collected data undergoes preprocessing, including morphological analysis and removal of stop words, to prepare it for text mining. Subsequently, the data is subjected to in-depth analysis using techniques such as word frequency analysis and topic modeling. Text mining allows for effective analysis of large-scale textual data, enabling the identification of macroscopic trends and patterns that may be difficult to discern through traditional qualitative research methods. This methodological approach is expected to provide new insights into the changes in South Korea's multicultural policies and social perceptions. Furthermore, it aims to contribute to deriving policy implications for a successful transition to a multicultural society in the future. By employing text mining techniques on a comprehensive corpus of news articles spanning over two decades, this study offers a novel perspective on the evolving landscape of multiculturalism in South Korea, bridging the gap between qualitative insights and quantitative analysis in this critical area of social research.