TY - GEN
T1 - Threshold models for competitive influence in social networks
AU - Borodin, Allan
AU - Filmus, Yuval
AU - Oren, Joel
PY - 2010
Y1 - 2010
N2 - The problem of influence maximization deals with choosing the optimal set of nodes in a social network so as to maximize the resulting spread of a technology (opinion, product-ownership, etc.), given a model of diffusion of influence in a network. A natural extension is a competitive setting, in which the goal is to maximize the spread of our technology in the presence of one or more competitors. We suggest several natural extensions to the well-studied linear threshold model, showing that the original greedy approach cannot be used. Furthermore, we show that for a broad family of competitive influence models, it is NP-hard to achieve an approximation that is better than a square root of the optimal solution; the same proof can also be applied to give a negative result for a conjecture in [2] about a general cascade model for competitive diffusion. Finally, we suggest a natural model that is amenable to the greedy approach.
AB - The problem of influence maximization deals with choosing the optimal set of nodes in a social network so as to maximize the resulting spread of a technology (opinion, product-ownership, etc.), given a model of diffusion of influence in a network. A natural extension is a competitive setting, in which the goal is to maximize the spread of our technology in the presence of one or more competitors. We suggest several natural extensions to the well-studied linear threshold model, showing that the original greedy approach cannot be used. Furthermore, we show that for a broad family of competitive influence models, it is NP-hard to achieve an approximation that is better than a square root of the optimal solution; the same proof can also be applied to give a negative result for a conjecture in [2] about a general cascade model for competitive diffusion. Finally, we suggest a natural model that is amenable to the greedy approach.
UR - http://www.scopus.com/inward/record.url?scp=78650879916&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-17572-5_48
DO - 10.1007/978-3-642-17572-5_48
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AN - SCOPUS:78650879916
SN - 3642175716
SN - 9783642175718
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 539
EP - 550
BT - Internet and Network Economics - 6th International Workshop, WINE 2010, Proceedings
T2 - 6th International Workshop on Internet and Network Economics, WINE 2010
Y2 - 13 December 2010 through 17 December 2010
ER -