Threshold Models for Competitive Influence in Social Networks
- Allan BorodinAffiliated withDepartment of Computer Science, University of Toronto
- , Yuval FilmusAffiliated withDepartment of Computer Science, University of Toronto
- , Joel OrenAffiliated withDepartment of Computer Science, University of Toronto
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  about a general cascade model for competitive diffusion.
Finally, we suggest a natural model that is amenable to the greedy approach.
- Threshold Models for Competitive Influence in Social Networks
- Book Title
- Internet and Network Economics
- Book Subtitle
- 6th International Workshop, WINE 2010, Stanford, CA, USA, December 13-17, 2010. Proceedings
- pp 539-550
- Print ISBN
- Online ISBN
- Series Title
- Lecture Notes in Computer Science
- Series Volume
- Series ISSN
- Springer Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
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