The Non-Linear Impact of Green Space Recreational Service Performance on Residents’ Emotional States in High-Density Cities

Amid accelerating global high-density urbanization, two pressing challenges have emerged: shrinking green space supplies in built-up areas and growing demand for residents’ emotional well-being. Notably, green spaces’ recreational function plays a pivotal role in alleviating emotional distress. This study aims to systematically assess Green Space Recreation Service Performance (GRSP) and unravel its non-linear impact on residents’ emotional states. Using Shijiazhuang—a representative high-density city in China—as a case study, we developed a GRSP evaluation framework integrating supply–demand balance and utilization efficiency. Natural Language Processing (NLP) techniques parsed social media texts, with continuous emotional scores quantifying residents’ emotional states. Finally, a Gradient Boosting Decision Tree (GBDT) model empirically explored the links between GRSP indicators and emotional states. Results show significant spatial differentiation and supply–demand mismatch in Shijiazhuang’s central urban GRSP: peripheral new districts have abundant green space supply but low utilization efficiency, while central built-up areas face insufficient supply paired with high usage intensity. Residents’ self-reported emotional health correlates with green space accessibility and crowding levels, with park distribution equity as the dominant driver. GRSP’s impact on emotional states exhibits non-linearities, threshold effects, and distinct interactions among core indicators. This study identifies key GRSP indicators influencing emotional states, clarifies their non-linear interaction mechanisms and critical thresholds, and provides empirical evidence for advancing emotional health theories in high-density urban contexts.