Getting the Right Spin: A Theory of Value of Social Networks

I examine the problem of maximizing the spread of information in a context where users of a network decide which piece of information is shared. A company thus provides initial information to some users and they then choose what to share to their neighbours. These actions of sharing and choosing produce the characteristics of word-of-mouth advertising over time. I then answer the two following questions: what is the best word-of-mouth campaign that the company can perform and second, what is the value of such a campaign? The optimal solution can be understood as a Nash Equilibria that maximizes the concentration of the initial information to a small group of users. Such solution contrasts with standard measures of user influence and I show that they can sometime be seriously misleading. I provide an exact solution for a wide class of generic network topologies and an algorithm to compute it in polynomial time.