  Gossip protocols form the basis of many smart collective adaptive systems.
They are a class of fully decentralised, simple but robust protocols for the
distribution of information throughout large scale networks with hundreds or
thousands of nodes. Mean field analysis methods have made it possible to
approximate and analyse performance aspects of such large scale protocols in an
efficient way. Taking the gossip shuffle protocol as a benchmark, we evaluate a
recently developed refined mean field approach. We illustrate the gain in
accuracy this can provide for the analysis of medium size models analysing two
key performance measures. We also show that refined mean field analysis
requires special attention to correctly capture the coordination aspects of the
gossip shuffle protocol.
