  We study the problem of election control through social influence when the
manipulator is allowed to use the locations that she acquired on the network
for sending \emph{both} positive and negative messages on \emph{multiple}
candidates, widely extending the previous results available in the literature
that study the influence of a single message on a single candidate. In
particular, we provide a tight characterization of the settings in which the
maximum increase in the margin of victory can be efficiently approximated and
of those in which any approximation turns out to be impossible. We also show
that, in simple networks, a large class of algorithms, mainly including all
approaches recently adopted for social-influence problems, fail to compute a
bounded approximation even on very simple networks, as undirected graphs with
every node having a degree at most two or directed trees. Finally, we
investigate various extensions and generalizations of the model.
