Academic

Recently, a paper co-authored by Dr. Li Boxuan, a faculty member of the School of International Organizations, as the corresponding author, was published in the international journal THE BRITISH JOURNAL OF POLITICS AND INTERNATIONAL RELATIONS. The paper, titled International network analysis based on big data: The case of economic cooperation among the G20, has Dr. Luo Hang, a tenured associate professor at Peking University, as its first author.

Using big data on economic cooperation events from 2000 to 2024, combined with a network structural change point detection algorithm, the paper analyzes the evolution of economic interactions among G20 countries. The study finds that while trade relations among G20 countries have grown increasingly close, the structural network of their economic cooperation has shown a trend toward fragmentation. Furthermore, the paper constructs weighted centrality measures based on the circuit model and random walks to capture the dynamic evolution of national power. This research offers a complementary perspective on observing economic interactions between countries, distinct from traditional approaches that rely solely on trade volume or static institutional data.

*The British Journal of Politics and International Relations is published by the Political Studies Association (PSA) and ranks in the SSCI Q1 category for Political Science (36/325) and International Relations (15/170) in 2024–2025.

Abstract of this paper:

How the structure of the international economic cooperation network among the G20 countries has evolved over the past quarter century, and what are the roles and power levels of different countries in the network? We collect big data on economic cooperation events among the G20 countries from 2000 to 2024, and divide the 25 years into four periods using structure changepoint detection algorithms to separately construct international economic cooperation networks. We calculate and compare the multifaceted characteristics of the G20 economic cooperation network and trade network based on network analysis. At the macrolevel of network structure, we find that even when trade relations among the G20 countries became closer, economic cooperation among them became more distant. At the mesolevel of group classification, the result of community detection and the disparity of edge weight of the G20 economic cooperation network and trade network show clear but different regional characters. At the microlevel of power distribution, we measure and compare the power levels of the G20 countries in the economic cooperation network and their dynamics over time using weighted centrality indices based on current flow and random walks. By combining network analysis and event big data, we study economic interactions between countries in a unique approach that differs from traditional approaches employing trade volume or institutional data (e.g. free trade agreements).

Reprinted Source: https://www.sis.pku.edu.cn/news641/5981a1d2943644e1870e529d1e4a6bde.htm

Link to this paper: https://doi.org/10.1177/13691481251378912