We use the k-core decomposition to visualize large scale complex networks in
two dimensions. This decomposition, based on a recursive pruning of the least
connected vertices, allows to disentangle the hierarchical structure of
networks by progressively focusing on their central cores. By using this
strategy we develop a general visualization algorithm that can be used to
compare the structural properties of various networks and highlight their
hierarchical structure. The low computational complexity of the algorithm,
O(n+e), where 'n' is the size of the network, and 'e' is the number of edges,
makes it suitable for the visualization of very large sparse networks. We apply
the proposed visualization tool to several real and synthetic graphs, showing
its utility in finding specific structural fingerprints of computer generated
and real world networks