Unveiling Dynamics in Climate Disaster Information Transmission Across Regions: A Variance Decomposition Network Approach


Modeling the dynamic transmission of climate disaster information during these events is vital for effective disaster preparation, response, and recovery. This study uses Hurricane Ida as a case study and Twitter (currently branded as X) as a social sensor to construct a disaster information network that captures climate disaster information transmission across regions. Analyzing the co-movement of region-specific hurricane-related tweet trends that reflect unobservable disaster information in each region, we decompose the forecast error variance and covariance matrix to develop a weighted and directed information network adjacency matrix. We identify 79 sub-state regions with high flood risk but low hurricane information indegree. While most disaster information exchange occurs within each region, cross-region exchange closely aligns with snapshots of the Facebook friendship, SafeGraph mobility, and pre-existing migration networks. Notably, it diverges from the baseline Twitter communication network, highlighting the vital role of social-emotional connections in disseminating disaster information compared to other types of information. Disaster location and local population size predict disaster information indegree and outdegree, and the pre-existing migration network mediates the spread of disaster information. The disaster information network exhibits a higher proportion of unexplained variations compared to other social networks, underscoring the importance of collecting supplementary real-time data through social sensing.

Sébastien Box-Couillard
Sébastien Box-Couillard
Ph.D. Candidate in Applied Economics

I am a Ph.D. candidate in Agricultural and Consumer Economics at the University of Illinois Urbana-Champaign. My research interests lie at the intersection of environmental and urban economics. I am particularily interested in interactions between inequality, discrimination, housing markets and natural disasters.