The Internet Map

 The Internet map is developed by Ruslan Enikeev.He is a Russian data-visualization designer.In his project "The Internet Map" he has mapped websites according to its levels of activity and traffic. The 'Internet Map' shows each website as a circle, sized according to levels of web traffic. Websites's positioning is based on the different sites their visitors switch to and from. A circle's color indicates the country to which it relates. Type a URL into the box on the left to see how it compares to other sites, and click on 'about' to read more about how the graphic was built.


Ruslan Enikeev says," Like any other map, The Internet map is a scheme displaying objects’ relative position; but unlike real maps (e.g. the map of the Earth) or virtual maps (e.g. the map of Mordor), the objects shown on it are not aligned on a surface. Mathematically speaking, The Internet map is a bi-dimensional presentation of links between websites on the Internet. Every site is a circle on the map, and its size is determined by website traffic, the larger the amount of traffic, the bigger the circle. Users’ switching between websites forms links, and the stronger the link, the closer the websites tend to arrange themselves to each other".

The Internet Map

The map of the Internet is a photo shot of the global network as of end of 2011. It encompasses over 350 thousand websites from 196 countries and all domain zones. Information about more than 2 million links between the websites has joined some of them together into topical clusters. As one might have expected, the largest clusters are formed by national websites, i.e. sites belonging to one country. For the sake of convenience, all websites relative to a certain country carry the same color. For instance, the red zone at the top corresponds to Russian segment of the net, the yellow one on the left stands for the Chinese segment, the purple one on the right is Japanese, the large light-blue central one is the American segment, etc.

Importantly, clusters on the map are semantically charged, i.e. they join websites together according to their content. For example, a vast porno cluster can be seen between Brazil and Japan as well as a host of minor clusters uniting websites of the same field or similar purposes.