Mapping urban soundscape patterns using user-generated content: A place model approach to acoustic environment perception.

Abstract

Urban acoustic environments significantly influence quality of life, prompting a paradigm shift from noise reduction to soundscape design that considers human perception. This study investigates urban soundscape perceptions using social media data to understand how acoustic environments reflect urban spatial characteristics. We collected Korean-language Twitter texts from 156 points of interest in Seoul's central and southeastern neighborhoods from October to November 2020. The collected texts were preprocessed through text cleaning and morphological analysis, then classified using an urban soundscape taxonomy based on Canter's place model that integrates physical setting, activity, and meaning dimensions. The results revealed that activity-related soundscapes (79.4%) dominated all target areas, and strong negative correlations between indoor, mechanical, and behavioral soundscapes suggest a spatial separation of acoustic zones by urban function. Especially, historical central districts (22.0%) showed a higher proportion of meaning-related soundscapes compared to modern commercial districts (13.4%). K-means clustering further identified three soundscape types: infrastructure-dominated, socially vibrant, and commercial indoor-focused zones. By combining social media analysis with spatial patterns, the study provides a scalable tool for urban planners to understand how citizens experience urban soundscapes, offering data-driven insights for contextualized urban design.