Examination of risk factors in bus accidents: merging the AcciMap framework with natural language processing methods

Combining CoSENT-enhanced sentence embeddings, unsupervised clustering, and AcciMap-based network quantification enables scalable extraction and systemic interpretation of causal factors from unstructured bus-accident narratives. Results indicate that strengthening regulatory enforcement, improving enterprise safety management and managerial accountability, and targeting frontline driver behaviors should be coordinated to break multi-level risk propagation chains. The pipeline offers a reproducible method for automated, policy-relevant causal analysis and can guide prioritized interventions and monitoring in urban passenger transport safety.