Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis

Our findings demonstrated that linguistic markers in publicly shared pain-related discourse show distinct and predictable differences across regions with varying opioid mortality risks. These linguistic patterns reflect underlying psychological, social, and structural factors that contribute to opioid vulnerability. Importantly, they offer a scalable, real-time resource for identifying at-risk communities. Harnessing social media language analytics can strengthen early detection systems, guide geographically targeted public health messaging, and inform policy efforts aimed at reducing opioid-related harm and improving pain management equity.