Understanding Citizens' and Local Governments' Digital Communications During Natural Disasters: The Case of Snowstorms

Abstract

A growing number of citizens and local governments have embraced the use of Twitter to communicate during natural disasters. Studies have shown that online communications during disasters can be explained using crisis communication taxonomies. However, such taxonomies are broad and general, and offer little insight into the detailed content of the communications. In this paper, we propose a semi-automatic framework to extract and compare, in retrospect, the digital communication footprints of citizens and governments during disasters. These footprints, which characterize the topics discussed during a disaster at different spatio-temporal scales, are computed in an unsupervised manner using topic models, and manually labelled to identify specific issues affecting the population. The end objective is to offer detailed information about issues affecting citizens during natural disasters and to compare these against local governments' communications. We evaluate the framework using Twitter communications from 18 snowstorms (including two blizzards) on the US east coast.