  The ability to compare complex systems can provide new insight into the
fundamental nature of the processes captured in ways that are otherwise
inaccessible to observation. Here, we introduce the $n$-tangle method to
directly compare two networks for structural similarity, based on the
distribution of edge density in network subgraphs. We demonstrate that this
method can efficiently introduce comparative analysis into network science and
opens the road for many new applications. For example, we show how the
construction of a phylogenetic tree across animal taxa according to their
social structure can reveal commonalities in the behavioral ecology of the
populations, or how students create similar networks according to the
University size. Our method can be expanded to study a multitude of additional
properties, such as network classification, changes during time evolution,
convergence of growth models, and detection of structural changes during
damage.
