Measurement of social networks for innovation within community disaster resilience

Joanna Wilkin, Eloise Biggs, Andrew J. Tatem

Research output: Contribution to journalReview article

1 Citation (Scopus)

Abstract

Disaster risk reduction (DRR) research has long recognised that social networks are a vital source of support during and after a shock. However, the quantification of this social support, primarily through its recognition as social capital, has proven problematic as there is no singular method for its measurement, invalidating the credibility of studies that try to correlate its effects with community disaster resilience. Within the wider resilience field, research that specifically utilises social networks as the focus of analysis is evolving. This paper provides a critical synthesis of how this developing discourse is filtering into community disaster resilience, reviewing empirical case studies from the Global South within DRR that use social network analysis and connectivity measurement. Our analysis of these studies indicates that a robust methodology utilising social network analysis is emerging, which offers opportunity for research cross-comparability. Our review also finds that without this bottom-up mapping, the implementation of top-down preparedness policy and procedures are likely to fail, resulting in the advocation of social network analysis as a critical methodology in future resilience research and policy planning.

Original languageEnglish
Article number1943
JournalSustainability (Switzerland)
Volume11
Issue number7
DOIs
Publication statusPublished - 1 Apr 2019

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social network
Disasters
resilience
disaster
innovation
Electric network analysis
Innovation
network analysis
community
methodology
social capital
quantification
field research
credibility
social support
connectivity
Planning
planning
discourse
analysis

Cite this

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title = "Measurement of social networks for innovation within community disaster resilience",
abstract = "Disaster risk reduction (DRR) research has long recognised that social networks are a vital source of support during and after a shock. However, the quantification of this social support, primarily through its recognition as social capital, has proven problematic as there is no singular method for its measurement, invalidating the credibility of studies that try to correlate its effects with community disaster resilience. Within the wider resilience field, research that specifically utilises social networks as the focus of analysis is evolving. This paper provides a critical synthesis of how this developing discourse is filtering into community disaster resilience, reviewing empirical case studies from the Global South within DRR that use social network analysis and connectivity measurement. Our analysis of these studies indicates that a robust methodology utilising social network analysis is emerging, which offers opportunity for research cross-comparability. Our review also finds that without this bottom-up mapping, the implementation of top-down preparedness policy and procedures are likely to fail, resulting in the advocation of social network analysis as a critical methodology in future resilience research and policy planning.",
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Measurement of social networks for innovation within community disaster resilience. / Wilkin, Joanna; Biggs, Eloise; Tatem, Andrew J.

In: Sustainability (Switzerland), Vol. 11, No. 7, 1943, 01.04.2019.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Measurement of social networks for innovation within community disaster resilience

AU - Wilkin, Joanna

AU - Biggs, Eloise

AU - Tatem, Andrew J.

PY - 2019/4/1

Y1 - 2019/4/1

N2 - Disaster risk reduction (DRR) research has long recognised that social networks are a vital source of support during and after a shock. However, the quantification of this social support, primarily through its recognition as social capital, has proven problematic as there is no singular method for its measurement, invalidating the credibility of studies that try to correlate its effects with community disaster resilience. Within the wider resilience field, research that specifically utilises social networks as the focus of analysis is evolving. This paper provides a critical synthesis of how this developing discourse is filtering into community disaster resilience, reviewing empirical case studies from the Global South within DRR that use social network analysis and connectivity measurement. Our analysis of these studies indicates that a robust methodology utilising social network analysis is emerging, which offers opportunity for research cross-comparability. Our review also finds that without this bottom-up mapping, the implementation of top-down preparedness policy and procedures are likely to fail, resulting in the advocation of social network analysis as a critical methodology in future resilience research and policy planning.

AB - Disaster risk reduction (DRR) research has long recognised that social networks are a vital source of support during and after a shock. However, the quantification of this social support, primarily through its recognition as social capital, has proven problematic as there is no singular method for its measurement, invalidating the credibility of studies that try to correlate its effects with community disaster resilience. Within the wider resilience field, research that specifically utilises social networks as the focus of analysis is evolving. This paper provides a critical synthesis of how this developing discourse is filtering into community disaster resilience, reviewing empirical case studies from the Global South within DRR that use social network analysis and connectivity measurement. Our analysis of these studies indicates that a robust methodology utilising social network analysis is emerging, which offers opportunity for research cross-comparability. Our review also finds that without this bottom-up mapping, the implementation of top-down preparedness policy and procedures are likely to fail, resulting in the advocation of social network analysis as a critical methodology in future resilience research and policy planning.

KW - Community disaster resilience

KW - Connectivity

KW - Data

KW - Disaster risk reduction

KW - Innovation

KW - Social network analysis

KW - Social network mapping

KW - Social networks

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DO - 10.3390/su11071943

M3 - Review article

VL - 11

JO - Sustainability (Switzerland)

JF - Sustainability (Switzerland)

SN - 2071-1050

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