  Patterns often appear in a variety of large, real-world networks, and
interesting physical phenomena are often explained by network topology as in
the case of the bow-tie structure of the World Wide Web, or the small world
phenomenon in social networks. The discovery and modelling of such regular
patterns has a wide application from disease propagation to financial markets.
In this work we describe a newly discovered regularly occurring striation
pattern found in the PageRank ordering of adjacency matrices that encode
real-world networks. We demonstrate that these striations are the result of
well-known graph generation processes resulting in regularities that are
manifest in the typical neighborhood distribution. The spectral view explored
in this paper encodes a tremendous amount about the explicit and implicit
topology of a given network, so we also discuss the interesting network
properties, outliers and anomalies that a viewer can determine from a brief
look at the re-ordered matrix.
