  We study the dynamics involved in a sparse random network model. We extend
the standard mean-field approximation for the dynamics of a random network by
employing the path-integral approach. The result indicates that the
distribution of the variable is essentially identical to that obtained from
globally coupled oscillators with random Gaussian interaction. We present the
results of a numerical simulation of the Kuramoto transition in a random
network, which is found to be consistent with this analysis.
