Applying text mining and semantic network analysis to investigate effects of perceived crowding in the service sector

Semantic analysis is becoming increasingly important not only in computing but also the business world. The purpose of current study to apply semantic network service industry, one economic sectors. To learn more about crowded environment sector, interviewed customers and employees by using dyad approach sector. data collected was analyzed a text mining Python library Ucinet software. through interviews multiple techniques like sentiment analysis, centrality CONCOR analysis. results from two sets with consumers revealed certain effects behavior that they exhibit environment. When providing services environment, experience variety behavioral changes, whether due physical, psychological, emotional, habitual, or work-related factors. Additionally, findings show crowding has an emotional psychological impact on customers’ responses. offers implications for intelligence.