  We introduce a model of information dissemination in signed networks. It is a
discrete-time process in which uninformed actors incrementally receive
information from their informed neighbors or from the outside. Our goal is to
minimize the number of confused actors - that is, the number of actors who
receive contradictory information. We prove upper bounds for the number of
confused actors in signed networks and in equivalence classes of signed
networks. In particular, we show that there are signed networks where, for any
information placement strategy, almost 60\% of the actors are confused.
Furthermore, this is also the case when considering the minimum number of
confused actors within an equivalence class of signed graphs.
