  Recently there has been a lot of interest in monitoring and identifying
changes in dynamic networks, which has led to the development of a variety of
monitoring methods. Unfortunately, these methods have not been systematically
compared; moreover, new methods are often designed for a specialized use case.
In light of this, we propose the use of simulation to compare the performance
of network monitoring methods over a variety of dynamic network changes. Using
our family of simulated dynamic networks, we compare the performance of several
state-of-the-art social network monitoring methods in the literature. We
compare their performance over a variety of types of change; we consider both
increases in communication levels, node propensity change as well as changes in
community structure. We show that there does not exist one method that is
uniformly superior to the others; the best method depends on the context and
the type of change one wishes to detect. As such, we conclude that a variety of
methods is needed for network monitoring and that it is important to understand
in which scenarios a given method is appropriate.
