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Related Experiment Video

Updated: May 8, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

International migration network: topology and modeling.

Giorgio Fagiolo¹, Marina Mastrorillo

¹LEM, Sant'Anna School of Advanced Studies, Pisa, 56127 Italy.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|August 16, 2013

Summary

This study analyzes the international migration network (IMN) using complex network theory. Findings reveal socioeconomic, geographic, and political factors significantly shape global migration patterns.

Area of Science:

Sociology
Network Science
Economics

Background:

International migration is a complex global phenomenon.
Understanding migration patterns is crucial for policy and social science.
Previous studies often focused on bilateral flows rather than network structures.

Purpose of the Study:

To analyze the international migration network (IMN) using a complex-network perspective.
To characterize the structure and evolution of the IMN from 1960 to 2000.
To identify key drivers shaping the IMN's topology.

Main Methods:

Defining the IMN as a weighted-directed graph of countries and migrant stocks.
Characterizing the binary and weighted network architecture.
Employing a gravity model to explain network structure.

Related Experiment Videos

Last Updated: May 8, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Main Results:

The IMN exhibits modularity and small-world properties (disassortativity, high clustering).
Weighted network statistics follow a power-law distribution.
A gravity model effectively explains a significant portion of the IMN's topological structure.

Conclusions:

Socioeconomic, geographical, and political factors are primary drivers of the IMN's structure.
Local network properties play a lesser role compared to macro-level factors.
Network analysis provides valuable insights into global migration dynamics.