Presentation
Mining Recurring Themes in Firefighter Decision-Making: An LDA Topic Modeling Analysis
SessionPoster Session 2
DescriptionThe research on firefighter decision-making has expanded over the years, but the findings are scattered, and gaps persist in understanding the factors affecting the cognitive performance of firefighters. It is essential to reveal the latent cognitive, physical, and operational aspects in firefighter decision-making. This study employs Latent Dirichlet Allocation (LDA) topic modeling to analyze firefighter decision-making by mining themes from abstracts of 57 research articles. The findings revealed eight distinct topics, each characterized by ten key words. The thematic analysis of the topics identified four major clusters: the effect of safety and training on decision-making, the impact of overall health on firefighter performance, the influence of stress on decision-making, and the role of expertise in firefighter decision-making. Findings provide a thorough understanding of current research trends and inform training design and future research in firefighter decision-making.
Event Type
Poster
TimeWednesday, October 15th5:30pm - 6:30pm CDT
LocationRiverside East
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