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.
|Date of creation:||Sep 2012|
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- Constanza Fosco & Annick Laruelle & Angel Sánchez, 2011. "Turnout Intention And Random Social Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 31-53.
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- Bala, Venkatesh & Goyal, Sanjeev, 1998.
"Learning from Neighbours,"
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Wiley Blackwell, vol. 65(3), pages 595-621, July.
- Ting Liu & Pasquale Schiraldi, 2012. "New product launch: herd seeking or herd preventing?," Economic Theory, Springer, vol. 51(3), pages 627-648, November.
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