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The 1995–2018 global evolution of the network of amicable and hostile relations among nation-states

Political Science

The 1995–2018 global evolution of the network of amicable and hostile relations among nation-states

O. Askarisichani, A. K. Singh, et al.

This research, conducted by Omid Askarisichani, Ambuj K. Singh, Francesco Bullo, and Noah E. Friedkin, delves into the intricate evolution of international relationships from 1995 to 2018. Utilizing the ICEWS dataset, the authors uncover how positive and negative interactions between countries conform to Structural Balance Theory, while also introducing a new probabilistic micro-dynamic model that traces shifts in global opinions.

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~3 min • Beginner • English
Abstract
There has been longstanding interest in the evolution of positive and negative relationships among countries. An interdisciplinary field of study, Structural Balance Theory, has developed on the dynamics of such appraisal systems. However, the advancement of research in the field has been impeded by the lack of longitudinal empirical data on large-scale networks. We construct the networks of international amicable and hostile relations occurring in specific time-periods in order to study the global evolution of the network of such international appraisals. Here we present an empirical evidence on the alignment of Structural Balance Theory with the evolution of the structure of this network, and a model of the probabilistic micro-dynamics of the alterations of international appraisals during the period 1995–2018. Also remarkably, we find that the trajectory of the Frobenius norm of sequential transition probabilities, which govern the evolution of international appraisals among nations, dramatically stabilizes.
Publisher
Communications Physics
Published On
Jul 28, 2020
Authors
Omid Askarisichani, Ambuj K. Singh, Francesco Bullo, Noah E. Friedkin
Tags
international relations
Structural Balance Theory
network evolution
probabilistic model
ICEWS dataset
core-periphery structure
transition probabilities
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