This study aims to analyze differences in domestic and international disaster research trends. We first performed topic modeling on 20,477 papers published in three domestic and 12 international journals over the last 21 years (2000-2020) and then visualized the trends. Based on the extracted topics and keywords, we analyzed keyword networks using Gephi. Research in domestic journals mainly revolved around natural disasters like earthquakes, fire, and flooding. In contrast, international journals spotlighted policy-based topics such as disaster governance and community resilience. Meanwhile, globally, building and civil engineering research has shrunk in recent five years (we refer to this as a cold topic). On the other hand, in the past five years, fire and flood research has appeared more frequently in domestic journals, while international journals have presented more articles on community resilience, risk perception, and behavior (we refer to this as a hot topic). Results of this research can provide suggestions about the directions domestic disaster research should develop in the future.
Overcoming Language Barriers: Assessing the Potential of Machine Translation and Topic Modeling for the Comparative Analysis of Multilingual Text Corpora
