2025/08/06 by Dasom Hong, Sumin Han, Youngjun Park +2 · 1 voice
Economics, Econometrics and Finance · Environmental Science · Social Sciences · #Human Mobility and Location-Based Analysis #Land Use and Ecosystem Services #Spatial and Panel Data Analysis
paper · pdf · doi:10.1111/area.70037
openalex publication_date 2025/08/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/05/21
Abstract The recent proliferation of locative mobile devices and location‐based services has sparked geographers' interest in how such ‘spatial media’ reshape individual's mobility, spatial experiences, and perceptions. Notably, the urban and digital geography literature has highlighted the relationship between spatial media, gentrification, and urban redevelopment processes, suggesting the potential of spatial media to generate new capitalist opportunities and increase the profitability of urban spaces. In this context, this study examines how spatial media reconfigure urban land value patterns, which have been primarily explained through urban forms. To this end, we employ the spatial capital model, a regression model that predicts property value patterns using variables associated with urban forms. We demonstrate that models incorporating both offline spatial configurations and online popularity outperform the spatial capital model relying solely on physical urban layouts, thereby underscoring the role of spatial media in reshaping the spatial arrangements of capital in urban centres. Using a machine learning algorithm, we construct and compare spatial capital models and regression models with variables reflecting online popularity on Instagram to estimate land prices in three neighbourhoods in Seoul: Yeonnam‐dong, Seongsu‐dong, and Gyeongridan‐gil. These regions have experienced a surge in property values following heightened visibility on Instagram since the mid‐2010s. Our findings indicate that the performance of models incorporating Instagram data exhibit superior predictive performance relative to traditional spatial capital models. Instagram‐related variables also demonstrates greater explanatory power than conventional variables related to urban forms in predicting land price change rates. Additionally, the influence of online popularity on Instagram varies across time and space, closely aligned with the phase of development in online popularity within each area. In conclusion, spatial media have increasingly shaped urban land value patterns, while the dynamics between spatial media, urban forms, and property values can vary alongside the development of online popularity in specific regions.