A Big Data Analysis of Non-Face-to-Face K-Performance contents Consumption Characteristics in the MZ Generation

Purpose: This study aims to examine the consumption trends of non-face-to-face K-performance contents by the MZ generation during the COVID-19 pandemic period(January 2020-December 2022) through big data analysis, and to propose strategic directions for the performing arts industry. Methods: Using text data collected from online platforms—including social media, blogs, news, and online communities—this study conducted quantitative analyses such as text mining (word frequency, TF-IDF, semantic network analysis, and CONCOR) to identify the MZ generation’s consumption behaviors and key trends in non-face-to-face K-performances contents. Results: The findings indicated that the MZ generation places high emphasis on cutting-edge technologies(metaverse, immersive technology), real-time interaction, fan community reinforcement, and marketing strategies in non-face-to-face K-performance contents. The results also suggest that ‘Hi-flex’ performance models, which combine offline and online channels, have great potential for global market expansion. Conclusion: As digital natives who seek interactive and value-oriented consumption experiences, the MZ generation plays a pivotal role in the successful implementation of non-face-to-face performances. Incorporating VR/AR-based immersive technology, personalized services, fandom community engagement, and hybrid performance models from the planning stage can contribute to sustainable growth and enhanced global competitiveness in the performing arts industry