Investigating the “Fever” of Northeast Cultural Tourism from Two Perspectives and Exploring the Road to Changhong: Based on Data Mining and Explainable Machine Learning

Since 2023, the cultural tourism industry in North-east China has risen rapidly, significantly promoting the economic growth of Heilongjiang, Jilin, and Liaoning provinces. However, the seasonal characteristics and limited sustainability of tourism resources in Northeast China are still urgent problems to be solved. Based on data mining and explainable machine learning, this study studies the cognitive views of tourists and residents on the development of cultural tourism, aiming to make a modest contribution to the “ever-popular” road of cultural tourism in Northeast China. In this study, we used factor analysis and SEM structural equation model to explore the current situation of cultural tourism and tourist experience in Northeast China. Elastic Net and ADASYN were used to solve the problems of multicollinearity and sample imbalance of data, and the results showed that the accuracy, stability and optimization of the decision tree were better, and the contribution of each influencing factor to tourists' travel intention was analyzed by combining with SHAP, and the K-Prototypes clustering was used to depict the portrait of potential tourists. Finally, the non-whole rank-rank sum ratio comprehensive evaluation method was used to evaluate residents' sense of identity.