As part of my last job, I got a chance to work with network visualization and analysis as it related to biodiversity research in the EU. In the past month or so, I have also been working on a few fun side projects like the one below: a network map of Europe.
In the map below, each point in the network (or "node") represents a European country that is a member of the United Nations. Two countries are linked in the network if they share a border; for example, at the top right Turkey and Greece share a border and so are linked together. Some non-European countries - such as China - are included because they share a border with a European country.
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| A Network Map of Europe (Full-size, Creative Commons-licensed image available here) |
The size of a node is determined by how many other countries it shares a border with. On one extreme, Russia borders 14 other countries and is the largest node in the network. On the other end of the spectrum, the island nations of Malta (top-left corner) and Iceland (top-right corner) do not border any countries, and are visualized as tiny, free-floating nodes.
The network also contains five "communities" of nodes that are closely connected to each other, color-coded below as green, dark blue, light blue, dark orange, and light orange. These communities were defined by running a statistical test (for "modularity") on the free network visualization software Gephi.
This map was just for fun, but what could techniques like this offer to researchers or policy-makers working on European issues?
Sources
Border information is drawn from Wikipedia. Unlike the Wikipedia article, I did not include Kosovo because it is not a member of the United Nations and its sovereignty is disputed.
