  In traditional models for word-of-mouth recommendations and viral marketing,
the objective function has generally been based on reaching as many people as
possible. However, a number of studies have shown that the indiscriminate
spread of a product by word-of-mouth can result in overexposure, reaching
people who evaluate it negatively. This can lead to an effect in which the
over-promotion of a product can produce negative reputational effects, by
reaching a part of the audience that is not receptive to it.
  How should one make use of social influence when there is a risk of
overexposure? In this paper, we develop and analyze a theoretical model for
this process; we show how it captures a number of the qualitative phenomena
associated with overexposure, and for the main formulation of our model, we
provide a polynomial-time algorithm to find the optimal marketing strategy. We
also present simulations of the model on real network topologies, quantifying
the extent to which our optimal strategies outperform natural baselines
