Designing cascading disaster networks by means of natural language processing

Abstract

In this study, we propose a method for evaluating cascading disasters using natural language processing to comprehensively and objectively extract causal relations between disaster events based on newspaper articles and construct cascading disaster networks. The applicability of this method is illustrated by employing data extracted from Japanese newspaper articles on the Great Hanshin-Awaji Earthquake and the Great East Japan Earthquake. Both disasters showed complex chain relations, and the proposed method extracted escalation points such as the “stoppage of factory production in the stricken area” for the Great Hanshin-Awaji Earthquake and “scheduled power outages outside the stricken areas” for the Great East Japan Earthquake based on each network structure. When matched with Alexander's magnitude scale for cascading disasters, both these catastrophic events were confirmed to reach Level 5.