Harnessing Twitter (X) with AI-enhanced natural language processing for disaster management: Insights from California wildfire

Social media usage surges during natural disasters, offering critical insights into public sentiment and needs. This study leverages artificial intelligence (AI) and advanced natural language processing (NLP) techniques to analyze Twitter (X) data from the 2018 California Camp Fire. By combining sentiment analysis, emotion classification, and humanitarian topic classification, we provide a nuanced understanding of social responses. Tweets were categorized into six humanitarian topics and twelve emotion classes, revealing significant regional and temporal variations. Our findings show shifts from immediate safety concerns to recovery and support as the disaster progressed. Results highlight key differences in emotional responses between California and other U.S. states, emphasizing the role of proximity in shaping social media discourse. These AI-driven insights can inform disaster management strategies by optimizing communication, resource allocation, and real-time decision-making. This research underscores the value of AI-powered social media analysis in enhancing disaster preparedness, response, and recovery efforts.