Accident‐Related Help‐Seeking Posts From Truck Drivers: Topic Modelling, Attribution, and Response Analysis

ABSTRACT

In high‐risk industries, occupational risks are often manifested through everyday operational disruptions rather than catastrophic events alone. In freight transportation, recurrent incidents such as vehicle breakdowns, cargo problems, and traffic accidents generate substantial demands for assistance and coordination, yet the broader patterns underlying these accident‐related situations remain insufficiently understood. Drawing on 17,696 accident‐related help‐seeking posts contributed by 14,437 truck drivers to China's largest online Q&A platform between 2018 and 2020, this study examines how occupational risks are expressed and organised within digital interaction spaces. Structural topic modelling identifies 50 latent accident‐related topics, which are subsequently organised through network‐based community detection into five structurally distinct accident‐related scenarios spanning traffic accident, emergency mobility restoration, localised situational assistance, roadside operational recovery, and institutional liability and compensation handling. These scenarios characterise how assistance needs and resource requirements are matched under accident‐related conditions, varying along two dimensions: the urgency of support and the temporal stage of problem handling. Multinomial logistic regression shows that engagement with different accident‐related scenarios is systematically associated with driver and vehicle characteristics. Cross‐scenario comparisons further reveal variation in both response volume and response effectiveness, indicating that different accident‐related situations generate distinct patterns of collective response on digital platforms. The findings demonstrate that platform‐generated help‐seeking posts provide a valuable source of occupational risk information beyond conventional accident datasets. By organising fragmented accident‐related incidents into recurring scenarios and examining their associations with driver characteristics and collective response patterns, the study develops a scenario‐based perspective on occupational risk in freight transportation. It further shows that online participation does not necessarily translate into effective assistance, revealing important differences in the problem‐solving capacity of online occupational communities across accident‐related situations.