Zhang Mingyuan, Chen Shenwen, Du Wenbo, Cao Xianbin, Li Daqing, Zhang Jun, Havlin Shlomo
School of Electronic and Information Engineering, Beihang University, Beijing 100191, China.
School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China.
PNAS Nexus. 2022 Dec 9;2(1):pgac289. doi: 10.1093/pnasnexus/pgac289. eCollection 2023 Jan.
Changing attitudes in diplomatic relations is a common feature of international politics. However, such changes may trigger risky domino-like cascades of "friend-to-enemy" transitions among other counties and yielding catastrophic damage that could reshape the global network of international relationships. While previous attention has been focused on studying single pairs of international relationships, due to the lack of a systematic framework, it remains still unknown whether, and how, a single transition of attitude between two countries could trigger a cascade of attitude transitions among other countries. Here, we develop such a framework and construct a global evolving network of relations between country pairs based on 70,756,728 international events between 1,225 country pairs from January 1995 to March 2020. Our framework can identify and quantify the cascade of transitions following a given original transition. Surprisingly, weaker transitions are found to initiate most of the largest cascades. We also find that transitions are not only related to the balance of the local environment, but also global network properties such as betweenness centrality. Our results suggest that these transitions have a substantial impact on bilateral trade volumes and scientific collaborations. Our results reveal reaction chains of international relations, which could be helpful for designing early warning signals and mitigation methods for global international conflicts.
外交关系中态度的转变是国际政治的一个常见特征。然而,这种转变可能引发其他国家间类似多米诺骨牌效应的危险的“从朋友到敌人”的转变级联,并造成可能重塑全球国际关系网络的灾难性破坏。尽管此前的关注焦点一直是研究单一的国际关系对,但由于缺乏系统框架,两国间单一的态度转变是否会以及如何引发其他国家间的态度转变级联,仍然未知。在此,我们开发了这样一个框架,并基于1995年1月至2020年3月期间1225对国家间的70756728起国际事件,构建了一个全球国家对间关系的演化网络。我们的框架能够识别并量化给定初始转变后的转变级联。令人惊讶的是,发现较弱的转变引发了大多数最大规模的级联。我们还发现,转变不仅与当地环境的平衡有关,还与诸如中介中心性等全球网络属性有关。我们的结果表明,这些转变对双边贸易量和科学合作有重大影响。我们的结果揭示了国际关系的反应链,这可能有助于设计全球国际冲突的预警信号和缓解方法。