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May 15, 2026Applied SciencesOpen Access

Network Analysis of Chemical Accident Causation Based on Text Mining

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Authors

JLJikun LiuMXMeiqi XieCWCuixia Wang

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Overview

This randomized trial analyzes causative factors of chemical accidents, highlighting key elements for effective prevention.

Key Points

  • The aim is to identify key causative factors of chemical accidents and understand their characteristics.
  • Text mining techniques extracted causative factors from accident investigation reports.
  • Factors were classified using an enhanced Human–Machine–Environment–Management framework.
  • Random undersampling and association rule mining were applied 30 times with different random seeds.
  • The causation network displays small-world and scale-free properties, indicating strong connections among factors.
  • Top three causative factors identified include illegal production organization (D6), pipeline rupture (B5), and unsafe work practices (D12).
  • PageRank centrality analysis showed accident-related nodes in the network's core, with variations across different accident types.

Cite This Study

Liu et al. (2026) studied this question.

synapsesocial.com/papers/6a06b983e7dec685947ac2b9https://doi.org/10.3390/app16104696
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Also Consider

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