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Updated: Feb 26, 2026
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Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
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Mapping urban soundscape patterns using user-generated content: A place model approach to acoustic environment
1KAIST Urban Design Lab, KAIST Smart City Research Center, Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
Plos One
|February 24, 2026
Summary
This study used social media data to analyze urban soundscapes in Seoul. Activity-related sounds dominate, with distinct acoustic zones identified by urban function and historical context.
Area of Science:
- Urban planning and acoustic ecology
- Human-computer interaction and social media analytics
- Environmental psychology and spatial cognition
Background:
- Urban acoustic environments impact quality of life, shifting focus from noise reduction to holistic soundscape design.
- Understanding human perception of urban soundscapes is crucial for effective urban planning and design.
- Social media data offers a novel approach to capture and analyze public perception of urban acoustic environments.
Purpose of the Study:
- To investigate urban soundscape perceptions by analyzing social media data.
- To understand how acoustic environments reflect specific urban spatial characteristics.
- To develop a scalable tool for urban planners to assess citizen experiences of urban soundscapes.
Main Methods:
- Collected Korean-language Twitter data from 156 points of interest in Seoul (Oct-Nov 2020).
- Preprocessed text data (cleaning, morphological analysis) and classified soundscapes using a taxonomy based on Canter's place model (physical setting, activity, meaning).
- Applied K-means clustering to identify distinct urban soundscape types based on spatial and functional characteristics.
Main Results:
- Activity-related soundscapes constituted the majority (79.4%) across all analyzed areas.
- Negative correlations between indoor, mechanical, and behavioral soundscapes indicated functional spatial separation of acoustic zones.
- Historical districts exhibited a higher proportion of meaning-related soundscapes (22.0%) compared to modern commercial districts (13.4%).
- Identified three distinct soundscape clusters: infrastructure-dominated, socially vibrant, and commercial indoor-focused zones.
Conclusions:
- Social media analysis combined with spatial patterns provides data-driven insights for contextualized urban design.
- The study offers a scalable method for urban planners to understand citizen experiences of urban soundscapes.
- Findings highlight the importance of considering perceptual dimensions in urban soundscape design for improved quality of life.
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