Exploring the association between the built environment and positive sentiments of tourists in traditional villages in Fuzhou, China

开放的体验 地理 索引(排版) 中国 计算机科学 环境资源管理 社会经济学 心理学 环境科学 社会学 万维网 社会心理学 考古
作者
Zhengyan Chen,Honghui Yang,Yishan Lin,Jiahui Xie,Yuanqin Xie,Zheng Ding
出处
期刊:Ecological Informatics [Elsevier BV]
卷期号:80: 102465-102465 被引量:8
标识
DOI:10.1016/j.ecoinf.2024.102465
摘要

Promoting positive emotional experiences for tourists is crucial for sustaining development in rural areas. However, existing research has limited focus on the rural built environment, particularly in developing a framework to evaluate environmental sentiment on a small to medium scale with detailed indicators. This study addresses this gap by examining the impact of the rural built environment on tourists' emotions. Natural Language Processing (NLP) technologies are employed to analyze web text data and determine the average sentiment index for traditional villages in Fuzhou, China. Additionally, data on the built environment were acquired through the HRnet segmentation model and Matlab. To assess the association between environmental indicators and the sentiment index, we used eXtreme Gradient Boosting (XGBoost), the SHapley Additive exPlanation (SHAP) model, and ArcMap software. The study demonstrated that (1) the spatial distribution of the average sentiment index was significant. Houfu Village (9.91), Qianhu Village (9.88), and Ximen Village (9.75) had the highest scores, while Doukui Village (−0.85), Jiji Village (0.2), and Qiaodong Village (0.55) had the lowest. (2) The indicators that have the most significant impact on sentiment are Openness, Greenness, and Color Complexity, with a contribution value above 0.7—followed by Enclosure, Visual Entropy, and Ground Exposure, with a contribution between 0.5 and 0.7. Furthermore, analyzing the interaction mechanism of the indicators showed a non-linear relationship. The environmental characteristics associated with high emotional index scores are openness in the range of 0.2 to 0.5, greenness in the range of 0.4 to 0.6, and color complexity in the range of 0.3 to 0.5. This study provides observations pertinent to the sustainable development of traditional village environments. The findings contribute to an understanding of how these environmental elements might be effectively designed to improve tourists' sentiment in rural settings.
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