Using Social Media to Model Community-Based Behavioral Response During Public Health Emergencies: A Case Study of the 2023 Canadian Wildfires

Abstract

New York City (NYC) experienced severe air pollution from Canadian wildfires in June 2023, disrupting travel and daily activities. This study analyzed public reactions to evacuation, indoor activities, shopping, and recreation using geotagged X posts during the air pollution crisis. Geotagged posts were reverse geocoded to census blocks and spatially joined with socioeconomic and demographic data from the U.S. census and American Community Survey. The dataset initially comprised 0.59 million geotagged X posts from 66,858 unique users in NYC over a 1-week period. After relevance filtering, the final dataset included 10,258 posts from 10,258 unique users on wildfire-related travel and activity discussions. Public reactions were analyzed using a BERT-based natural language processing model, whereas a gender–race model inferred users’ gender and racial identities based on their first and last names. A multinomial logit model assessed how socioeconomic and demographic factors influenced activity discussions during the crisis. The findings revealed demographic differences in responses. For instance, females were less likely to discuss evacuation and essential trips, possibly owing to continued workplace operations despite hazardous conditions. Racial differences were also evident, with Asians more frequently mentioning evacuation and commuting, whereas African Americans showed lower engagement in discussions about social and recreational activities. Socioeconomic disparities further influenced response patterns, as lower-income and less-educated groups expressed fewer concerns about evacuation, highlighting potential barriers to crisis awareness and preparedness. These insights emphasize the need for targeted communication strategies and equitable health interventions to ensure that emergency responses effectively reach vulnerable populations during environmental crises.