Effects of cultural landscape service features in national forest parks on visitors’ sentiments: A nationwide social media-based analysis in China

Abstract

National Forest Parks (NFPs) represent the highest level of the forest park system in China and have long been considered to cultivate positive experiences among visitors through their rich cultural services. However, there is limited knowledge of the relationship between the cultural dimension of landscape services (CLSs) in NFPs and visitors’ positive experiences. This study represents the first effort to investigate the effects of NFP CLSs on visitors’ expressed sentiments and aims to further identify the relative importance of various CLS features. A total of 267 NFPs across 31 provinces in China were selected as case studies, and approximately 300,000 visitors’ online comments from a widely used travel platform (CTrip) were obtained for sentiment analysis using natural language processing. A novel systematic framework for assessing CLSs was proposed, encompassing five principal features and 19 indicator subcategories. Ordinary least-squares and spatial regression models were used to reveal associations between NFP CLSs and expressed sentiments, whereas the XGBoost model and Shapley Additive exPlanations (SHAP) values were employed to identify the relative importance of NFP CLS features. Three major findings were observed: First, the feature scoring of CLSs in NFPs was unevenly distributed across the country, with scores along the eastern seaboard relatively higher than those inland in the northwest. Second, beneficial associations between the five principal CLS features and visitors’ expressed sentiments were suggested. Third, the influence of landscape aesthetics was particularly prominent in promoting visitors’ positive sentiments, followed by education, physical activities and health, recreation and tourism, and cultural heritage and spiritual practices. These findings provide valuable insights for health-oriented NFP management, policies, and planning.