An Analysis of Aesthetic Perception of Karst Landscapes Based on Social Media UGC Data: A Case Study of Huangguoshu Scenic Area

Abstract

Karst terrain has become a tourism hotspot due to its unique natural landscape and aesthetic value. However, research on the aesthetic perception of tourists in karst scenic areas is still insufficient. This study selected Huangguoshu Scenic Area as a case study, using User Generated Content (UGC) data from tourism social media to capture tourist photos of the scenic area as analysis samples. By extracting points of interest (POI) from photos, ArcGIS 10.2 was used for kernel density analysis, NVivo 11 was used for encoding analysis of photo content, and UCINET 6 software was used for social network analysis of node data to explore tourists' aesthetic perception of the Huangguoshu landscape. The study revealed the following findings: (1) Tourists' aesthetic attention mainly focuses on the combination of "mountain water (waterfall) vegetation" landscape elements formed by special terrain and landforms, while the attention to cultural and cultural landscapes is relatively low; (2) There are differences in the popularity of different scenic spots within Huangguoshu Scenic Area, with the Great Waterfall Scenic Area being the most popular, followed by Tianxing Bridge Scenic Area and Doupotang Scenic Area. The range of tourists shows a clear pattern of seasonal distribution, with the most concentrated tourists in summer and the most scattered in autumn. (3) The overall emotional tendency of tourists towards the Huangguoshu landscape is positive, and the amount and intensity of positive emotions exceed negative emotions. Negative emotions mainly stem from overcrowding during flood season and dissatisfaction during dry season. The conclusion of this study has practical guiding significance for optimizing resource allocation and improving tourist experience in Huangguoshu Scenic Area, and provides valuable reference information for the protection and development of other karst scenic areas.