  Current models for opinion dynamics typically utilize a Poisson process for
speaker selection, making the waiting time between events exponentially
distributed. Human interaction tends to be bursty, though, having higher
probabilities of either extremely short waiting times or long periods of
silence. To quantify the burstiness effects on the dynamics of social models,
we place in competition two groups exhibiting different speakers' waiting-time
distributions. These competitions are implemented in the binary Naming Game,
and show that the relevant aspect of the waiting-time distribution is the
density of the head rather than that of the tail. We show that even with
identical mean waiting times, a group with a higher density of short waiting
times is favored in competition over the other group. This effect remains in
the presence of nodes holding a single opinion that never changes, as the
fraction of such committed individuals necessary for achieving consensus
decreases dramatically when they have a higher head density than the holders of
the competing opinion. Finally, to quantify differences in burstiness, we
introduce the expected number of small-time activations and use it to
characterize the early-time regime of the system.

Physics and Society;Social and Information Networks