Competitive contagion in networks

We develop a game-theoretic framework for the study of competition between firms who have budgets to “seed” the initial adoption of their products by consumers located in a social network. The payoffs to the firms are the eventual number of adoptions of their product through a competitive stochastic diffusion process in the network. This framework yields a rich class of competitive strategies, which depend in subtle ways on the stochastic dynamics of adoption, the relative budgets of the players, and the underlying structure of the social network. We identify a general property of the adoption dynamics — namely, decreasing returns to local adoption — for which the inefficiency of resource use at equilibrium (the Price of Anarchy) is uniformly bounded above, across all networks. We also show that if this property is violated the Price of Anarchy can be unbounded, thus yielding sharp threshold behavior for a broad class of dynamics. We also introduce a new notion, the Budget...

• Type: Journal
• Year: 2012
• Where: STOC
• Authors: Sanjeev Goyal, Michael Kearns
• Keywords: Algorithmic Game Theory, Algorithms, Budget Multiplier, Initial Adoption, STOC 2012