Inferring the Character of Urban Commercial Areas from Age-biased Online Search Results How place recommendation data can reveal dynamic Seoul neighborhoods

Abstract

We analyze the consumer-age-specific patterns of restaurant preferences in commercial areas of Seoul, through the mining of place recommendation results from the Naver Place online service. We calculate indices for 188 distinct areas of Seoul measuring the heterogeneity of taste across age groups, and the dominance of any one age group over the general options presented to the public. Our results suggest that both high-traffic and rapidly changing commercial areas present diverse options appealing to all age groups, and that this diversity is primarily driven by the tastes of younger age groups. Recognizing these patterns may help stakeholders predict gentrification and proactively shape neighborhood transformation from business turnover. This study contributes to the broader literature on applying online behavioral data to study urban economic activity.