  We consider a model of Bayesian persuasion with one informed sender and
several uninformed receivers. The sender can affect receivers' beliefs via
private signals, and the sender's objective depends on the combination of
induced beliefs.
  We reduce the persuasion problem to the Monge-Kantorovich problem of optimal
transportation. Using insights from optimal transportation theory, we identify
several classes of multi-receiver problems that admit explicit solutions, get
general structural results, derive a dual representation for the value, and
generalize the celebrated concavification formula for the value to
multi-receiver problems.
