Evidence map›Paper›PMID 41639222›Full record

ArticleScientific reports2026

Unraveling hierarchical penetration mechanisms and coupling relationships of safety risks in major transportation infrastructure construction using text mining and complex networks.

Wei Liu, XiaoLong Kang, Qing Ye, Junhao Xie

Abstract read
In one paragraph

Article in Scientific reports, 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

4 authors.

Wei LiuSchool of Civil Engineering and Architecture, East China Jiaotong University, Nanchang, 330013, China. liuweijx13@163.com.
XiaoLong KangSchool of Civil Engineering and Architecture, East China Jiaotong University, Nanchang, 330013, China. 15770634485@163.com.
Qing YeSchool of Civil Engineering and Architecture, East China Jiaotong University, Nanchang, 330013, China.
Junhao XieSchool of Civil Engineering and Architecture, East China Jiaotong University, Nanchang, 330013, China.

Funding

Jiangxi Province 2025 Postgraduate Innovation Special Funds Project YC2025-S487Jiangxi Provincial Natural Science Foundation 20242BAB204088National Natural Science Foundation of China project 72261012
6 · The paper itself

Abstract

The continuous expansion and increasing complexity of major transportation infrastructure construction have led to frequent safety accidents during construction. To address the limitations of traditional methods in safety risk management and to reveal the hierarchical penetration mechanisms and coupling relationships of risk factors, this study established a new paradigm for understanding safety risks in transportation infrastructure construction by integrating text mining and complex network theory, based on 244 construction safety accidents that occurred in China between 2010 and 2023. First, text mining was used to extract 101 key features related to safety accidents in major transportation infrastructure construction from raw data, and these features were utilized to develop an improved Human Factors Analysis and Classification System (HFACS) model. Subsequently, a co-occurrence matrix was employed to quantify the frequency and strength of associations among factors, leading to the construction of a Safety Risk Network (SRN) with risk factors as nodes. By calculating the Multi-Feature Gravity Model (MCGM) value and the comprehensive degree C(i) for cross-validation, the following findings were revealed:① Inadequate safety training, though widely connected, have a weak global impact;② Explicit factors such as equipment defects are easily identifiable and are predominantly influenced by supervisory-level factors;③ Safety management in construction should focus on addressing systemic deficiencies at the organizational and supervisory levels rather than merely rectifying operational-level issues. Finally, a hierarchical blocking and proactive defense strategy was developed using the Bow-Tie Model, providing a quantitative decision-making basis for enhancing the intelligence of safety management in major transportation engineering projects.

Indexed as

Data MiningSafetySafety ManagementTransportationChinaHumansModels, TheoreticalRisk FactorsComplex networkConstruction safetyHFACS modelMajor transportation infrastructureText mining

Identifiers

PMID41639222
PMCPMC12923838

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.