Random linear network coding (RLNC) unicast protocol is analyzed over a rapidly-changing network topology. We model the probability mass function (pmf) of the dissemination time as a sequence of independent geometric random variables whose success probability changes with every successful reception of an innovative packet. We derive a tight approximation of the average networked innovation probability conditioned on network dimension increase. We show through simulations that our approximations for the average dissemination time and its pmf are tight. We then propose to use a RLNC-based broadcast dissemination protocol over a general dynamic topology where nodes are chosen for transmission based on average innovative information that they can provided to the rest of the network. Simulation results show that information disseminates considerably faster as opposed to standard RLNC algorithm where nodes are chosen uniformly at random.