Research on the emotional experience of online tourists in Zhangjiajie based on text mining and LDA-FDEMATEL
Cheng-Ru Wu, Ming-Han Chiang, Bao-Hui Huang, Hung-Lung Lin, Yanran HuangOnline travel platforms generate extensive user-generated content (UGC), yet the causal structure of tourists’ emotional experiences remains insufficiently understood. This study examines Zhangjiajie Scenic Area by integrating Latent Dirichlet Allocation (LDA) with fuzzy DEMATEL and DANP to extract emotional themes and identify their hierarchical relationships within a destination system. Results reveal a three-layer structure of emotional experience formation: an input layer (management systems, service processes, and vegetation landscapes), a contextual conditioning layer (water, mountain, architectural landscapes, and temporal regulation), and an outcome layer (visitor activities, perceptions, evaluations, and impressions). These layers interact through a transformation process that shapes how environmental stimuli are converted into emotional responses. The findings demonstrate that emotional experience is systemically constructed through hierarchical causal interactions rather than isolated attributes. The study provides a structured framework for tourism emotion analysis and offers evidence-based implications for emotion-oriented destination management in nature-based tourism contexts.