Cablegate Network Similarity n:n

Look mum, moar data pr0n

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This visualization shows structural similarity between 4932 networks.

Each node is a network and each edge the structural similarity.

Some of these networks have identical structures.

The node size is the average weighted degree, or how similar the node is to it’s surrounding peers.

How it is done

Load the Cablegate reference network. Take the giant component and split it into smaller networks using community detection. Take the remaining components. Filter out networks with less then 10 nodes. Create a B-Matrix portrait for each network. Measure the matrix distance (or similarity) between each network (12.159,846 combinations). Create a weighted undirected graph were each node is a network and each edge the similarity. Use the distance measure as edge weight. Remove edges with an distance measure of > 0.12 (0 means the network is equal).

Result: a graph of 4932 nodes and 19163 edges.

What does it mean?

We will look at the structures behind each node in detail in a future posting but from the visualization we can make some conclusions.

Islands of isolated structures with all networks being identical

A larger component with 8-10 different structures gradually shifting between similar structures.

Source code and more soon…