Evidence map›Paper›PMID 42181984›Full record

SynthesisInternational journal of public health2026

A systematic review of enhancing urban disaster resilience for smart cities: from a perspective of social network analysis.

Yongzhu Zhang, Shiyao Zhu

Abstract readSystematic Review
In one paragraph

Synthesis in International journal of public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yongzhu ZhangSchool of Transportation and Civil Engineering, Nantong University, Nantong, China.
Shiyao ZhuSchool of Transportation and Civil Engineering, Nantong University, Nantong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study examines how Social Network Analysis (SNA) contributes to understanding and enhancing urban resilience, addressing the need to integrate social dimensions beyond technology-driven smart city approaches. Methods: A systematic literature review combining bibliometric and content analysis was conducted on 89 peer-reviewed articles to identify key themes, node types, and applications of SNA in resilience research. Results: Findings show that urban resilience is shaped by interactions among community, institutional, and infrastructure networks, though most studies focus on isolated network types. SNA applications have evolved from small-scale surveys to social media and multi-source data, yet longitudinal analyses remain limited. Highly central nodes are often assumed to enhance resilience, but causal relationships are rarely tested. Additionally, social ties, community engagement, and behavioral factors emerge as critical drivers, while challenges persist in data integration, dynamic analysis, and incorporating human behavior into network models. Conclusion: Advancing SNA for urban resilience requires integrating diverse data sources, longitudinal approaches, and behavioral insights to support more inclusive, adaptive, and evidence-based urban policy and disaster management strategies.

Indexed as

CitiesDisaster PlanningDisastersResilience, PsychologicalSocial Network AnalysisHumansSocial SupportUrban Populationmulti-agent networknetwork dynamicssmart citysocial network analysisurban resilience

Identifiers

PMID42181984
PMCPMC13195180

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.