Abstract
We present a novel way to characterize the structure of complex networks by
studying the statistical properties of the trajectories of random walks over
them. We consider time series corresponding to different properties of the
nodes visited by the walkers. We show that the analysis of the fluctuations of
these time series allows to define a set of characteristic exponents which
capture the local and global organization of a network. This approach provides
a way of solving two classical problems in network science, namely the
systematic classification of networks, and the identification of the salient
properties of growing networks. The results contribute to the construction of a
unifying framework for the investigation of the structure and dynamics of
complex systems.
Users
Please
log in to take part in the discussion (add own reviews or comments).