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In the latent voter model, which models the spread of a technology through asocial network, individuals who have just changed their choice have a latentperiod, which is exponential with rate $\lambda$, during which they will notbuy a new device. We study site and edge versions of this model on randomgraphs generated by a configuration model in which the degrees $d(x)$ have $3\le d(x) \le M$. We show that if the number of vertices $n \to\infty$ and $\logn \ll \lambda_n \ll n$ then the latent voter model has a quasi-stationary statein which each opinion has probability $\approx 1/2$ and persists in this statefor a time that is $\ge n^m$ for any $m<\infty$. Thus, even a very small latentperiod drastically changes the behavior of the voter model.

Latent Voter Model on Locally Tree-Like Random Graphs