Roadtrip! European highway network as a… well a network
In one of my previous posts I used network analysis to describe the Helsinki tram network. Now it’s time to up the ante and visualize the international E-road network that forms the skeleton of the European transit system!
Why? The network analysis approach opens new ways for discovering patterns in old subjects. For example every city is in average 15 cities away from each other and the diameter of Europe by road is 41 cities. Also while Paris, Warsaw and Moscow are the most central cities in Europe, the first two cities that can reach all of the other cities are Kiev and Rivne (all other cities in the network are max 20 steps away).
In the picture above the size of the city represents the number of it’s connections and the size of the city name represents the amount of shortest paths goes through it (betweenness centrality). The color of the city corresponds with its reversed closeness centrality: the deeper the color the more “close” to other cities the city is. It’s worth remembering that the distance between two cities is 1, so actual geography doesn’t apply here, only the connections. Also this graph only represents the connected network: some of the Central Asian roads are left out. Here is more detailed pdf, dataset (.net -file) available on request.
Networks visualized with Gephi