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A multiresolution framework for the analysis of community structure in international trade networks
Wonguk Cho1,2, Daekyung Lee3, Beom Jun Kim4
1Graduate School of Data Science, Seoul National University, Seoul, 08826, Republic of Korea.
Abstract:
International trade networks are complex systems that consist of overlapping multiple trade blocs of varying sizes. However, the resulting structures of community detection in trade networks often fail to accurately represent the complexity of international trade. To address this issue, we propose a multiresolution framework that integrates information from a range of resolutions to consider trade communities of different sizes and reveal the hierarchical structure of trade networks and their constituent blocks. In addition, we introduce a measure called multiresolution membership inconsistency for each country, which demonstrates the positive correlation between a country's structural inconsistency in terms of network topology and its vulnerability to external intervention in terms of economic and security functioning. Our findings show that network science-based approaches can effectively capture the complex interdependencies between countries and provide new metrics for evaluating the characteristics and behaviors of countries in both economic and political contexts.
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