Tourist Spatial-Temporal Behavior Model in Scenic Spot Based on Social Media Data

Social media data can effectively model tourist spatial-temporal behavior, revealing key patterns in scenic spot visitation. This study demonstrates that by analyzing posts from platforms like Sina Weibo, researchers can quantify passenger flow heterogeneity, identify popular routes, and assess stay-time intensity—without relying on traditional survey methods. Applied to the Temple of Heaven Park in Beijing, the model uncovered uneven distribution of tourist activity across different areas, with some zones experiencing significantly higher foot traffic. The findings suggest that social media-driven analysis offers a scalable, real-time tool for scenic spot planning and management, potentially optimizing visitor experiences while preserving cultural heritage.

YANG, Y., ZHANG, X., & MA, Y. (2019). Tourist Spatial-Temporal Behavior Model in Scenic Spot Based on Social Media Data. DEStech Transactions on Computer Science and Engineering, (cisnrc). https://doi.org/10.12783/dtcse/cisnrc2019/33310