Abstract
BACKGROUND: Major earthquakes are commonly visualized using Geographic Information Systems (GIS), with bubble maps scaled according to magnitude, depth, or casualty counts. This study investigates the hypothesis that countries most frequently mentioned in earthquake-related academic articles (CMEAs) correspond to those most impacted by significant seismic events. METHODS: Data on 27,100 major earthquakes (magnitude ≥ 5.5) from 1965 to March 2025 were obtained from the U.S. Geological Survey (USGS). Earthquake magnitudes were visualized using GIS bubble maps, and temporal trends were analyzed based on magnitude and year. In parallel, 24,974 earthquake-related articles published between 2015 and 2024 were retrieved from the Web of Science Core Collection (WoSCC). Ten key metadata elements were analyzed to identify the top 10 CMEAs. Kano diagrams were used to assess the relations between these countries, with articles mentions and publications, and those most affected by major earthquakes. Additionally, a bibliometric analysis using slope graphs was conducted to identify the most prominent article elements exhibiting upward publication trends. RESULTS: Key findings include the strongest earthquakes recorded were magnitude 9.1 events in Banda Aceh, Indonesia (2004), and off the coast of Tohoku, Japan (2011); earthquake frequency peaked in the years 2007 and 2010; China contributed the highest number of articles (6137; 24.57%), while the United States had the highest h-index (99 for the U.S. vs 78 for China); the correlation between the number of publications and the countries most severely affected by historical earthquakes was 0.232 (t = 1.167, P = .255), while the correlation between article mentions and those countries was 0.169 (t = 0.664, P = .517). CONCLUSION: This study does not support the hypothesis that countries most frequently discussed in earthquake-related literature correspond to those most affected by major earthquakes. However, the integrated use of hypothesis testing, slope graphs, Kano diagrams, and bibliometric summaries offers a robust framework for future research exploring publication trends in the context of natural disasters.