소셜 빅데이터를 활용한 청주 오스코(OSCO) MICE 인식 구조에 대한 탐색적 연구 = An Exploratory Study on the MICE Perception Structure of Cheongju OSCO Using Social Big Data

다국어 초록 (Multilingual Abstract)

Recently, social media–based big data has become a valuable tool for analyzing public perceptions and interest structures surrounding regional exhibitions and convention facilities. Particularly, studies on newly established MICE hubs in small and mid-sized cities are critical for effective policy formulation and strategic development. This study investigates public perceptions of the Cheongju Osong Convention Center (OSCO) using social media text data collected between January 1 and November 15, 2025. Key terms were extracted through text mining and analyzed using frequency analysis, centrality analysis, and CONCOR analysis. The results revealed that keywords such as exhibition fair, Osong, and events were central, reflecting OSCO’s role as a regional exhibition hub. CONCOR analysis further identified four semantic clusters: infrastructure-based, visitor experience–focused, experiential participation, and community-oriented information sharing. These findings indicate that OSCO is perceived as a multifunctional MICE platform that integrates local industry and daily life. The study provides empirical insights to inform future content development, operational strategies, and the formulation of regionally customized MICE policies.