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The small-world network of global protests.

Leonardo N Ferreira¹, Inho Hong², Alex Rutherford²

¹Center for Humans and Machines, Max Planck Institute for Human Development, Lentzeallee 94, 14195, Berlin, Germany. ferreira@mpib-berlin.mpg.de.

Scientific Reports

|September 29, 2021

Summary

Global protests spread rapidly through interconnected networks, becoming faster over time. This research uses extensive datasets to map protest diffusion patterns worldwide.

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Area of Science:

Social Sciences
Computational Social Science
Network Science

Background:

Protest diffusion is a global cascade process, but its mechanisms and extent remain poorly understood.
Existing research lacks comprehensive empirical analysis of large-scale protest spread dynamics.

Purpose of the Study:

To empirically investigate the spatial and temporal dynamics of global protest diffusion.
To analyze the network structure of protest events using large-scale datasets.

Main Methods:

Utilized protest data from GDELT and ICEWS, two extensive global datasets.
Constructed temporal networks of protest events by dividing the globe into grid cells.
Analyzed network properties such as small-world characteristics and average path lengths.

Main Results:

Temporal protest networks exhibit small-world properties, indicating efficient diffusion pathways.
Average path lengths in these networks have decreased over time, suggesting increased global connectivity.
Identified persistent temporal hubs that facilitate rapid protest spread across regions.

Conclusions:

Protest diffusion is facilitated by small-world network structures and temporal hubs.
The world is becoming increasingly interconnected in terms of protest dynamics, with events spreading more rapidly.
Findings support the hypothesis of quick global diffusion of protests from one region to another.