A Network Approach to Revealing Dynamic Succession Processes of Urban Land Use and User Experience

Abstract

One significant challenge to understanding the mechanisms of urban retail areas’ transition is limited data to trace a dynamic perspective of influential actors’ experience in an extended urban area. We overcome this gap by employing text mining to collect big text data from online blogs and propose a methodology to explore the dynamic spatial transformations and interactions across multiple adjacent retail areas. We study five retail areas that currently function as a major commercial hub in Seoul—the Hongdae area and its neighboring districts. We create co-occurrence networks of the text data to capture representative place images and user experiences. Our blog-word networks systematically capture the “invasion-succession” process in land-use transition during the commercialization of Hongdae’s neighboring districts. The process mirrors the history of spatial change in the areas, which once formed a small-scale, bohemian hip neighborhood that incubated indie culture and has now fully commercialized as a global tourist attraction. The commercial transition triggered by Hongdae’s cultural capital peaked with consumer experiences of “food and eating” dominating the whole area. Finally, the text networks signal gentrification in each commercial district near Hongdae, contributing to the current discourse on commercial gentrification by adding consumers’ perspectives.