TY - GEN
T1 - Strategyproof mechanisms for competitive influence in networks
AU - Borodin, Allan
AU - Braverman, Mark
AU - Lucier, Brendan
AU - Oren, Joel
PY - 2013
Y1 - 2013
N2 - Motivated by applications to word-of-mouth advertising, we consider a game-theoretic scenario in which competing advertisers want to target initial adopters in a social network. Each advertiser wishes to maximize the resulting cascade of influence, modeled by a general network diffusion process. However, competition between products may adversely impact the rate of adoption for any given firm. The resulting framework gives rise to complex preferences that depend on the specifics of the stochastic diffusion model and the network topology. We study this model from the perspective of a central mechanism, such as a social networking platform, that can optimize seed placement as a service for the advertisers. We ask: given the reported demands of the competing firms, how should a mechanism choose seeds to maximize overall efficiency? Beyond the algorithmic problem, competition raises issues of strategic behaviour: rational agents should not be incentivized to underreport their budget demands. We show that when there are two players, the social welfare can be 2-approximated by a polynomial-time strategyproof mechanism. Our mechanism is defined recursively, randomizing the order in which advertisers are allocated seeds according to a particular greedy method. For three or more players, we demonstrate that under additional assumptions (satisfied by many existing models of influence spread) there exists a simpler strategyproof e/e-1 -approximation mechanism; notably, this second mechanism is not necessarily strategyproof when there are only two players. Copyright is held by the International World Wide Web Conference Committee (IW3C2).
AB - Motivated by applications to word-of-mouth advertising, we consider a game-theoretic scenario in which competing advertisers want to target initial adopters in a social network. Each advertiser wishes to maximize the resulting cascade of influence, modeled by a general network diffusion process. However, competition between products may adversely impact the rate of adoption for any given firm. The resulting framework gives rise to complex preferences that depend on the specifics of the stochastic diffusion model and the network topology. We study this model from the perspective of a central mechanism, such as a social networking platform, that can optimize seed placement as a service for the advertisers. We ask: given the reported demands of the competing firms, how should a mechanism choose seeds to maximize overall efficiency? Beyond the algorithmic problem, competition raises issues of strategic behaviour: rational agents should not be incentivized to underreport their budget demands. We show that when there are two players, the social welfare can be 2-approximated by a polynomial-time strategyproof mechanism. Our mechanism is defined recursively, randomizing the order in which advertisers are allocated seeds according to a particular greedy method. For three or more players, we demonstrate that under additional assumptions (satisfied by many existing models of influence spread) there exists a simpler strategyproof e/e-1 -approximation mechanism; notably, this second mechanism is not necessarily strategyproof when there are only two players. Copyright is held by the International World Wide Web Conference Committee (IW3C2).
KW - Influence spread
KW - Mechanism design
KW - Social networks
UR - http://www.scopus.com/inward/record.url?scp=84893077012&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893077012&partnerID=8YFLogxK
U2 - 10.1145/2488388.2488402
DO - 10.1145/2488388.2488402
M3 - Conference contribution
AN - SCOPUS:84893077012
SN - 9781450320351
T3 - WWW 2013 - Proceedings of the 22nd International Conference on World Wide Web
SP - 141
EP - 151
BT - WWW 2013 - Proceedings of the 22nd International Conference on World Wide Web
PB - Association for Computing Machinery
T2 - 22nd International Conference on World Wide Web, WWW 2013
Y2 - 13 May 2013 through 17 May 2013
ER -