  Many real systems can be represented as networks whose analysis can be very
informative regarding the original system's organisation. In the past decade
community detection received a lot of attention and is now an active field of
research. Recently stability was introduced as a new measure for partition
quality. This work investigates stability as an optimisation criterion that
exploits a Markov process view of networks to enable multi-scale community
detection. Several heuristics and variations of an algorithm optimising
stability are presented as well as an application to overlapping communities.
Experiments show that the method enables accurate multi-scale network analysis.
