  The process of opinion formation through synthesis and contrast of different
viewpoints has been the subject of many studies in economics and social
sciences. Today, this process manifests itself also in online social networks
and social media. The key characteristic of successful promotion campaigns is
that they take into consideration such opinion-formation dynamics in order to
create a overall favorable opinion about a specific information item, such as a
person, a product, or an idea.
  In this paper, we adopt a well-established model for social-opinion dynamics
and formalize the campaign-design problem as the problem of identifying a set
of target individuals whose positive opinion about an information item will
maximize the overall positive opinion for the item in the social network. We
call this problem CAMPAIGN. We study the complexity of the CAMPAIGN problem,
and design algorithms for solving it. Our experiments on real data demonstrate
the efficiency and practical utility of our algorithms.
