비정형 데이터 시대의 정보시스템 연구 지형: 텍스트 마이닝의 확산과 지적 구조 분석 = The Landscape of Information Systems Research in the Era of Unstructured Data: The Expansion of Text Mining and Its Intellectual Structure

다국어 초록 (Multilingual Abstract)

The rapid growth of unstructured text data and the advancement of artificial intelligence technologies have significantly expanded the use of text mining in the field of information systems, but no systematic attempt has been made to analyze its intellectual structure and evolutionary processes. This study aims to identify the major themes, intellectual structures, and temporal changes in text mining research within information systems by analyzing 266 articles collected from the Web of Science database between 2009 and 2025. We conducted cluster and timeline analyses, and burst detection based䀀 on author co-citation analysis. The results revealed 13 research clusters and demonstrated a paradigm shift from early focuses on e-commerce and marketing toward more technology-oriented approaches, such as deep learning –based model optimization and healthcare data analytics. Furthermore, key models such as BERT, BioBERT, and Transformer were identified as turning points, suggesting new directions for text mining research. By providing a visual and quantitative overview of the research landscape and its evolution, this study offers both a theoretical foundation and empirical insights for future researchers in the information systems field.