What question did this study set out to answer?

The research aims to assess the social values of mega-scale green spaces by integrating new analytical frameworks.

April 19, 2026Open Access

Integrating SolVES and social media analytics to quantify social value spatial patterns and driving mechanisms in mega-scale green spaces

Key Points

The research aims to assess the social values of mega-scale green spaces by integrating new analytical frameworks.
Developed a dual-modal framework combining SolVES and social media analytics
Analyzed 1,086 reviews from social media for insights on social values
Assessed spatial structures and driving mechanisms in Luogang Park
Identified spatial polarization of social values with hot spots and cold spots
Proximity to roads significantly influenced social values
Ecological values received significantly less attention compared to aesthetic values

Abstract

Assessing the social values (SVs) of mega-scale green spaces (MSGs) in regenerated brownfields remains challenging due to spatial heterogeneity and perceptual dynamics. This study developed a dual-modal framework integrating the Social Values for Ecosystem Services (SolVES) model and social media analytics (1,086 reviews) to assess SVs in Luogang Park (1,270 ha), Hefei. Results revealed: (1) spatial polarization of SVs, with aesthetic and recreational hot spots clustering in cultural landmarks (mean value index, M-VI = 10), while biodiversity cold spots (M-VI = 6) were dispersed in ecological zones; (2) key drivers included proximity to roads (20–50 m buffer, contribution = 32.7%) and density of service facilities (p 0.8) and semantic perception, offering a transferable tool for equitable and multifunctional green space planning.

Integrating SolVES and social media analytics to quantify social value spatial patterns and driving mechanisms in mega-scale green spaces

Key Points

Abstract

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