Theme Modeling Study of Online Media Data for Ecotourism Based on Natural Language Processing

Against the backdrop of the proliferation of online media data, this study conducted an in-depth analysis of big data on eco-tour-related discussions in online media using natural language processing (NLP) techniques to identify public perceptions and preferences for eco-tours. By applying Latent Dirichlet Allocation (LDA) models and sentiment analysis methods based on sentiment lexicons, this study systematically analyzed online media data collected over a one-year period. The analysis revealed three core thematic discussion areas: tourist destination characteristics, ecological conservation awareness and national-level certification, and natural landscape and ecological diversity. The results of the sentiment analysis showed an overall positive bias in the online media discussions, indicating a positive public perception of eco-tourism destinations. The findings provide data support for sustainable scientific management of eco-tourism and a new methodology for online media big data analysis in the field of smart tourism.