A Study of Strategies for Promotion Workation Using Textmining

This study aims to understand public perception of workation, which is gaining attention as an alternative for regional revitalization. To achieve this, we analyzed big data related to workation using text mining techniques. Data was collected over the past year from Naver, Daum and Google using the big data collection and analysis platform, Textom. The collected data underwent a refinement process, and the top 100 keywords were selected for analysis. The study employed TF analysis, TF-IDF analysis, N-Gram analysis, semantic network analysis, and CONCOR analysis, utilizing tools such as Textom, UCINET6, and NetDraw. The analysis revealed that Jeju, Busan, travel, tourism, and support are significant keywords related to workation. Additionally, CONCOR analysis identified four clusters: policy-based, corporate participation, regional attractiveness, and infrastructure. These findings highlight the importance of various factors in the successful implementation of workation. Based on these findings, the study presents academic and practical implications. This research lays the foundational groundwork for studies on the new topic of workation and provides practitioners with a blueprint for developing workation systems. The insights gained from this study can guide policymakers and businesses in creating effective workation programs.