Alliances

This article asks why armed groups form high-end cooperation—training or intelligence sharing—even though such ties raise downstream political risks. The author develops a principal–agent theoretical logic: principals (providers of high-end support) mitigate risk by choosing agents who are skill-complementary but politically non-substitutable, while agents accept support only when it does not politically overshadow them. The study uses original network data on 53 groups in Northeast India from 1981–2021 and applies temporal exponential random graph models (TERGMs) to test the theory, producing evidence about organizational capacity differences, complementary attack portfolios, and constituency distinctiveness as correlates of high-end cooperation.

Structural balance theory and its extensions were applied to high-resolution alliance data from the virtual world Eve Online to analyze the dynamics of geopolitical relations. The analysis focused on how alliance size, relative power, and geographic proximity shape the prevalence and conditional behavior of triads formed from empirical political alliances.

Across the social sciences, pooling effects over long periods can produce faulty inferences when the underlying data generating process is dynamic. This work introduces a permutation-based, two-stage changepoint procedure designed for time series cross-sectional data to give researchers a principled way to detect when effect sizes truly change versus when they reflect routine stochastic fluctuation.

Localized network processes shape many political phenomena—yet they are poorly captured by methods that emphasize global network structure. Examples of these localized processes include: