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Structural Analysis and Mathematical Methods for Destabilizing Terrorist Networks Using Investigative Data Mining

von Nasrullah Memon, Henrik Legind Larsen

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The main idea is to use as a measure of the centrality of a node i the drop in the network efficiency caused by deactivation of the node. The importance I (nodei) of the ith [sic] node of the graph G is therefore:

I (nodei) ≡ Δ E = E (G) − E (G − nodei) , i = 1,...,N, (2)

Where G − nodei indicates the network obtained by deactivating nodei in the graph G. The most important nodes, i.e. the critical nodes are the ones causing the highest ΔE.

The main idea is to use as a measure of the centrality of a node i the drop in the network efficiency caused by the deactivation of the node. The importance I(nodei) of the ith node of the graph G is therefore:

I(nodei) ≡ ΔE = E(G) − E(G − nodei) , i = 1,...,N (2)

whereby G - nodei we indicate the network obtained by deactivating nodei in the graph G. The most important nodes, i.e. the critical nodes are the ones causing the highest ΔE.

 Anmerkungen The source is given in the previous paragraph in a way that suggests that the here documented paragraph summarizes content from the source. That it is taken verbatim from the source is not made clear, however. Sichter (Hindemith) Singulus

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The centrality measures address the question, “Who is the most important or central person in the network?” There are many answers to this question, depending on what we mean by important. Perhaps the simplest of centrality measures is degree centrality, also called simply degree.

Though simple, degree is often a highly effective measure of the influence or importance of a node: in many social settings people with more connections tend to have more power.

A more sophisticated version of the same idea is the so-called eigenvector centrality (which is also known as centrality of a centrality). Where degree centrality gives a [simple count of the number of connections a vertex has, eigenvector centrality acknowledges that not all connections are equal.]

[page 4]

Centrality measures address the question, “Who is the most important or central person in this network?” There are many answers to this question, depending on what we mean by important. Perhaps the simplest of centrality measures is degree centrality, also called simply degree.

[...]

Though simple, degree is often a highly effective measure of the influence or importance of a node: in many social settings people with more connections tend to have more power.

A more sophisticated version of the same idea is the so-called eigenvector centrality. Where degree centrality gives a simple count of the number of connections a vertex has, eigenvector centrality acknowledges that not all connections are equal.

 Anmerkungen Not a hint of the original source is given. Sichter (Graf Isolan), Hindemith

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