  We analyze order-disorder phase transitions driven by noise that occur in two
kinds of network models closely related to the self-propelled model proposed by
Vicsek et. al. to describe the collective motion of groups of organisms
[\emph{Phys. Rev. Lett.} {\bf 75}:1226 (1995)]. Two different types of noise,
which we call intrinsic and extrinsic, are considered. The intrinsic noise, the
one used by Vicsek et. al. in their original work, is related to the decision
mechanism through which the particles update their positions. In contrast, the
extrinsic noise, later introduced by Gr\'egoire and Chat\'e [\emph{Phys. Rev.
Lett.} {\bf 92}:025702 (2004)], affects the signal that the particles receive
from the environment. The network models presented here can be considered as
the mean-field representation of the self-propelled model. We show analytically
and numerically that, for these two network models, the phase transitions
driven by the intrinsic noise are continuous, whereas the extrinsic noise
produces discontinuous phase transitions. This is true even for the small-world
topology, which induces strong spatial correlations between the network
elements. We also analyze the case where both types of noise are present
simultaneously. In this situation, the phase transition can be continuous or
discontinuous depending upon the amplitude of each type of noise.
