Social Network Analysis of Corruption Structures: Adjacency Matrices Supporting the Visualization and Quantification of Layeredness

TL;DR

This paper advocates for applying social network analysis to corruption networks, emphasizing the use of adjacency matrices to visualize and quantify layered structures, thereby enhancing understanding of corruption dynamics.

Contribution

It introduces a network science approach to analyze corruption, focusing on adjacency matrices for visualization and quantification of layered corruption structures.

Findings

Network analysis reveals layered corruption structures

Adjacency matrices effectively visualize corruption networks

Quantitative measures improve understanding of corruption dynamics

Abstract

Often, corruption is described as taking place within or supported by a network: A collection of individuals structured in such a way as to enable the transaction of bribes for favors. Surprisingly, despite the network nomenclature, corruption is rarely analyzed from the network perspective using the tools of network science. Here, we will argue that analyzing corruption from the perspective of network science is beneficial to its understanding. In passing this chapter, a contribution to the Liber Amicorum in honor of Leo Huberts, then gives a very short introduction into social network analysis.