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Strategic Resource Allocation for Competitive Influence in Social Networks

Antonia Maria Masucci 1 Alonso Silva 2, 3, * 
* Corresponding author
1 HIPERCOM - High performance communication
Inria Paris-Rocquencourt, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, X - École polytechnique, CNRS - Centre National de la Recherche Scientifique : UMR
Abstract : One of the main objectives of data mining is to help companies determine to which potential customers to market and how many resources to allocate to these potential customers. Most previous works on competitive influence in social networks focus on the first issue. In this work, our focus is on the second issue, i.e., we are interested on the competitive influence of marketing campaigns who need to simultaneously decide how many resources to allocate to their potential customers to advertise their products. Using results from game theory, we are able to completely characterize the optimal strategic resource allocation for the voter model of social networks and prove that the price of competition of this game is unbounded. This work is a step towards providing a solid foundation for marketing advertising in more general scenarios.
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Submitted on : Friday, February 21, 2014 - 5:38:22 PM
Last modification on : Sunday, June 26, 2022 - 12:00:52 PM
Long-term archiving on: : Wednesday, May 21, 2014 - 12:15:47 PM


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  • HAL Id : hal-00950653, version 1
  • ARXIV : 1402.5388


Antonia Maria Masucci, Alonso Silva. Strategic Resource Allocation for Competitive Influence in Social Networks. Annual Allerton Conference on Communication, Control, and Computing, Oct 2014, Monticello, Illinois, United States. ⟨hal-00950653⟩



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