Evidence map›Paper›PMID 40065045›Full record

ArticleScientific reports2025

Assessment of urban seismic social vulnerability based on game theory combination and TOPSIS model: a case study of Changchun City.

Ming Ma, Yichen Zhang, Jiquan Zhang, Mingda Li, Jiale Zhu, Yang Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

6 authors.

Ming MaCollege of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130012, China.
Yichen ZhangCollege of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130012, China. zhangyc@ccit.edu.cn.
Jiquan ZhangInstitute of Natural Disaster Research, School of Environment, Northeast Normal University, Changchun, 130024, China.
Mingda LiCollege of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130012, China.
Jiale ZhuCollege of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130012, China.
Yang WangCollege of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130012, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Earthquakes, as one of the common natural phenomena in China, can directly lead to the collapse of buildings and trigger secondary effects such as landslides and tsunamis, often resulting in significant property losses and casualties. Therefore, conducting seismic risk assessments for regions holds great practical significance. Current disaster research typically requires a comprehensive consideration of the probabilities of disaster-causing factors, the instability of disaster-prone environments, and the vulnerability of disaster-bearing entities. In low seismic risk areas, studying the vulnerability of these entities is particularly important. However, most current research on social vulnerability (SV) in the context of earthquake disasters employs a single weighting method, which is largely constrained by data types and makes it challenging to fully reflect the characteristics of social vulnerability. To address this issue, this study focuses on Changchun City and constructs a comprehensive index system consisting of 12 indicators from the perspectives of exposure, sensitivity, and coping capacity. The TOPSIS model and game theory-based combined weighting method have been utilized to calculate the Social Vulnerability Index (SoVI). In this framework, subjective weights were determined using the G2 method, while objective weights were computed by integrating the CRITIC method and the entropy weighting method, thus forming a more scientifically reasonable weight distribution approach. The results of various weighting combinations demonstrate that the model can effectively express social vulnerability and further elucidate the influence of each indicator on regional vulnerability. The findings indicate that Chaoyang District and Yushu City exhibit high levels of social vulnerability. This paper conducts an in-depth analysis of the reasons behind this phenomenon and proposes corresponding policy recommendations, providing specific guidance for mitigating social vulnerability in these areas. This research is fundamentally significant for promoting the implementation of earthquake disaster prevention and reduction planning in Changchun City and fostering sustainable regional development.

Indexed as

CRITIC weightingEarthquake disasterEntropy methodGame theory combinationSocial vulnerabilityTOPSIS model

Identifiers

PMID40065045
PMCPMC11894114

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.