  In a network of reinforced stochastic processes, for certain values of the
parameters, all the agents' inclinations synchronize and converge almost surely
toward a certain random variable. The present work aims at clarifying when the
agents can asymptotically polarize, i.e. when the common limit inclination can
take the extreme values, 0 or 1, with probability zero, strictly positive, or
equal to one. Moreover, we present a suitable technique to estimate this
probability that, along with the theoretical results, has been framed in the
more general setting of a class of martingales taking values in [0, 1] and
following a specific dynamics.
