Tales of the 2025 Los Angeles Fire: Hotwash for Public Health Concerns in Reddit via LLM-Enhanced Topic Modeling
Sulong Zhou, Qunying Huang, Shaoheng Zhou, Yun Hang, Xinyue Ye, Aodong Mei, Kathryn Phung, Yuning Ye, Uma Govindswamy, Zehan Li

TL;DR
This study analyzes Reddit discussions during the 2025 Los Angeles wildfires using LLM-enhanced topic modeling to identify public health concerns and crisis narratives, providing insights for improved disaster response and communication.
Contribution
It introduces a scalable multi-layer framework combining topic modeling and LLMs for analyzing social media discourse during wildfires, along with the first annotated dataset for the 2025 LA fires.
Findings
Public health concerns are prominent in wildfire discourse.
Discourse volume aligns with real fire progression.
Mental health signals peak at night during crises.
Abstract
Wildfires have become increasingly frequent, irregular, and severe in recent years. Understanding how affected populations perceive and respond during wildfire crises is critical for timely and empathetic disaster response. Social media platforms offer a crowd-sourced channel to capture evolving public discourse, providing hyperlocal information and insight into public sentiment. This study analyzes Reddit discourse during the 2025 Los Angeles wildfires, spanning from the onset of the disaster to full containment. We collect 385 posts and 114,879 comments related to the Palisades and Eaton fires. We adopt topic modeling methods to identify the latent topics, enhanced by large language models (LLMs) and human-in-the-loop (HITL) refinement. Furthermore, we develop a hierarchical framework to categorize latent topics, consisting of two main categories, Situational Awareness (SA) and Crisis…
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Taxonomy
TopicsPublic Relations and Crisis Communication · Mental Health via Writing · Data-Driven Disease Surveillance
MethodsADaptive gradient method with the OPTimal convergence rate · Sparse Evolutionary Training
