Change Detection in Dynamic Political Networks: The Case of Sudan

Chapter
Part of the Intelligent Systems Reference Library book series (ISRL, volume 52)

Abstract

Social Network Change Detection (SNCD) algorithm is applied to detect abrupt change in political networks of Sudan. In particular, SNCD compares the longitudinal normalized network-level measures against a predetermined threshold value. These measures are density, average closeness, and average betweenness over different time periods. Data extracted from Sudan Tribune in 2003–2008 is presented in a form of yearly two-mode networks of agents and organizations. The result shows that SNCD detects abrupt changes that correspond to actual historical events. In particular, the analysis shows that the foreign-brokered signings of multiple peace agreements served as a political solidification point for political actors of Sudan. This was a catalyst that caused three leaders to have emerged and lead the more compartmentalized yet faction-cohesive political networks of Sudan.

Keywords

Change detection  Longitudinal network analysis Social network analysis Statistical process control Sudan 

Notes

Acknowledgments

This work is partly funded under a MURI—grant number N00014-08-1-1186 (Kathleen M. Carley, P.I.). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Office of Naval Research, or the U.S. government. I am also grateful for generous advice and thoughts from Jeffrey C. Johnson and Richard A. Lobban.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.California State University at FullertonFullertonUSA

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