Vivid London: Assessing the resilience of urban vibrancy during the COVID-19 pandemic using social media data

• A novel analytical framework is proposed to identify urban vibrancy. • Using Twitter and Flickr to assess the urban vibrancy resilience amid the pandemic. • Vibrant urban areas with certain common characteristics exhibit greater resilience. • Policy implications are provided for enhancing adaptability of urban vibrancy. Since COVID-19, the focus on urban resilience has intensified, particularly on cities' ability to adapt and recover while maintaining essential functions and liveability; however, few studies have examined the resilience of urban vibrancy during such health crises. This study investigates urban vibrancy resilience in Inner London during the COVID-19 pandemic using multi-sourced social media data (geo-tagged Twitter and Flickr). We propose an analytical framework based on space-time permutation scan statistics (STPSS) to identify spatiotemporal urban areas of interest (ST-AOIs), examining their spatial, temporal, and contextual characteristics. Our findings show that central neighbourhoods with transport hubs, educational and healthcare facilities, eateries, and financial centres exhibit greater resilience. These areas adapt by shifting active periods in response to disruptions. Additionally, we assess the varying resilience capacities of different types of points of interest. This research provides actionable insights for urban planners and policymakers by demonstrating how identifying characteristics of robust urban vibrancy can contribute to the resilience of cities and communities, particularly under normal conditions after COVID-19. The findings offer concrete strategies for integrating social media data into urban planning processes, enabling more responsive and adaptive governance that meets the dynamic needs of urban populations.

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Publication Details

Journal
Sustainable Cities and Society
Published
2024-09-15
DOI
https://doi.org/10.1016/j.scs.2024.105823
Citations
19
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
7.35
Controls
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article

Vivid London: Assessing the resilience of urban vibrancy during the COVID-19 pandemic using social media data

Siqin Wang, Meixu Chen, Yunzhe Liu, Zi Ye et al.
19 citations
Sustainable Cities and Society
Data-Driven Disease Surveillance
7.35
article

Vivid London: Assessing the resilience of urban vibrancy during the COVID-19 pandemic using social media data

Siqin Wang, Meixu Chen, Yunzhe Liu, Zi Ye, Wenjing Zhang
article en
19 citations

Abstract

• A novel analytical framework is proposed to identify urban vibrancy. • Using Twitter and Flickr to assess the urban vibrancy resilience amid the pandemic. • Vibrant urban areas with certain common characteristics exhibit greater resilience. • Policy implications are provided for enhancing adaptability of urban vibrancy. Since COVID-19, the focus on urban resilience has intensified, particularly on cities' ability to adapt and recover while maintaining essential functions and liveability; however, few studies have examined the resilience of urban vibrancy during such health crises. This study investigates urban vibrancy resilience in Inner London during the COVID-19 pandemic using multi-sourced social media data (geo-tagged Twitter and Flickr). We propose an analytical framework based on space-time permutation scan statistics (STPSS) to identify spatiotemporal urban areas of interest (ST-AOIs), examining their spatial, temporal, and contextual characteristics. Our findings show that central neighbourhoods with transport hubs, educational and healthcare facilities, eateries, and financial centres exhibit greater resilience. These areas adapt by shifting active periods in response to disruptions. Additionally, we assess the varying resilience capacities of different types of points of interest. This research provides actionable insights for urban planners and policymakers by demonstrating how identifying characteristics of robust urban vibrancy can contribute to the resilience of cities and communities, particularly under normal conditions after COVID-19. The findings offer concrete strategies for integrating social media data into urban planning processes, enabling more responsive and adaptive governance that meets the dynamic needs of urban populations.

Sustainable Cities and SocietyVol. 115
University of Southern California (US), University of Liverpool (GB), The University of Queensland (AU), MRC Centre for Environment and Health, Imperial College London (GB)
Openalex Percentile: Top 2%
Data-Driven Disease Surveillance
7.35
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