Abstract
We discuss how spreading processes on temporal networks are impacted by the
shape of their inter-event time distributions. Through simple mathematical
arguments and toy examples, we find that the key factor is the ordering in
which events take place, a property that tends to be affected by the bulk of
the distributions and not only by their tail, as usually considered in the
literature. We show that a detailed modeling of the temporal patterns observed
in complex networks can change dramatically the properties of a spreading
process, such as the ergodicity of a random walk process or the persistence of
an epidemic.
Users
Please
log in to take part in the discussion (add own reviews or comments).