Temporal Graph Theoretic Analysis of Geopolitical Dynamics in the U.S. Entity List

2025-10-24

AI Summary

Existing research lacks systematic analysis of the geopolitical dynamics underlying the U.S. Entity List, particularly its temporal evolution. This study addresses this gap by constructing the first event-driven dataset of foreign entity designations spanning 1998–2023 and proposing a multi-level temporal analytical framework that integrates temporal bipartite graph modeling, graph-theoretic analysis, and multi-scale network methods. The framework uncovers three critical dynamic patterns: (i) stepwise escalation in sanction intensity, (ii) persistent tenure inertia among listed entities, and (iii) coordinated multilateral/multisectoral pressure campaigns. Empirical validation demonstrates that the approach effectively detects geoeconomic strategic shifts, pacing changes, and alliance reconfigurations—phenomena obscured by static list analysis. By enabling granular, time-resolved assessment of export control regimes, this work establishes a scalable, dynamic paradigm for policy-oriented research on technology governance and economic statecraft.

Technology Category

• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Game Theory and Economic Paradigms: Mechanism Design
• Data Mining & Knowledge Management: Mining of Spatial, Temporal or Spatio-Temporal Data

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Web Mining and Content Analysis: Models for Web evolution
• Security and Privacy: Data transparency and provenance

Abstract

Export controls have become one of America's most prominent tools of economic statecraft. They aim to block rival countries' access to sensitive technologies, safeguard U.S. supply chains, protect national security, and shape geopolitical competition. Among various instruments, the U.S. Entity List has emerged as the most salient, yet its dynamics remain underexplored. This paper introduces a novel temporal graph framework that transforms the Entity List documents from a static registry of foreign entities of concern into a dynamic representation of geopolitical strategy. We construct the first event-based dataset of U.S. government foreign entity designations and model them as a temporal bipartite graph. Building on this representation, we develop a multi-level analytical approach that reveals shifting roles, enforcement strategy, and broader sanction ecosystems. Applied to 25 years of data, the framework uncovers dynamic patterns of escalation, persistence, and coordination that static views cannot capture. More broadly, our study demonstrates how temporal graph analysis offers systematic computational insights into the geopolitical dynamics of export controls.

Problem

• Analyzing dynamic patterns in U.S. Entity List designations
• Modeling geopolitical strategy through temporal graph framework
• Revealing escalation and coordination in export control enforcement

Innovation

• Temporal graph framework models Entity List dynamics
• Event-based dataset creates temporal bipartite graph
• Multi-level analysis reveals sanction patterns and strategies