  I review and extend the set of unifying principles, which allow comparing all
models of opinion dynamics within one single frame. Within the Global Unifying
Frame (GUF), any specific update rule chosen to study opinion dynamics for
discrete individual choices is recast into a probabilistic update formula. The
associated dynamics is deployed using a general probabilistic sequential
process, which is iterated via the repeated reshuffling of agents between
successive rounds of local updates. The related driving attractors and tipping
points are obtained with non-conservative regimes featuring both threshold and
threshold-less dynamics. Most stationary states are symmetry broken, but
fifty-fifty coexistence may also occur. A practical procedure is exhibited for
several versions of Galam and Sznajd models when restricted to the use of three
agents for the local updates. Comparing these various models, some are found to
be identical within the GUF. Possible discrepancies with numerical simulations
are discussed together with the difference between the GUF procedure and a mean
field approach.
