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Discount Targeting in Online Social Networks Using Backpressure-Based Learning

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Handbook of Optimization in Complex Networks

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 58))

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Abstract

Online social networks are increasingly being seen as a means of obtaining awareness of user preferences. Such awareness could be used to target goods and services at them. We consider a general user model, wherein users could buy different numbers of goods at a marked and at a discounted price. Our first objective is to learn which users would be interested in a particular good. Second, we would like to know how much to discount these users such that the entire demand is realized, but not so much that profits are decreased. We develop algorithms for multihop forwarding of discount coupons over an online social network, in which users forward such coupons to each other in return for a reward. Coupling this idea with the implicit learning associated with backpressure routing (originally developed for multihop wireless networks), we show how to realize optimal revenue. Using simulations, we illustrate its superior performance as compared to random coupon forwarding on different social network topologies. We then propose a simpler heuristic algorithm and using simulations, and show that its performance approaches that of backpressure routing.

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Acknowledgements

Research was funded in part by NSF grant CNS-0904520 and Qatar Telecom, Doha, Qatar.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA

    Srinivas Shakkottai

  2. Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA

    Lei Ying

Authors
  1. Srinivas Shakkottai
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  2. Lei Ying
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Correspondence to Srinivas Shakkottai .

Editor information

Editors and Affiliations

  1. Science and Engineering, Department of Computer and Information, University of Florida, Gainesville, 3260, Florida, USA

    My T. Thai

  2. Dept. Industrial & Systems, Engineering, University of Florida, Weil Hall 303, Gainesville, 32611-6595, Florida, USA

    Panos M. Pardalos

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Shakkottai, S., Ying, L. (2012). Discount Targeting in Online Social Networks Using Backpressure-Based Learning. In: Thai, M., Pardalos, P. (eds) Handbook of Optimization in Complex Networks. Springer Optimization and Its Applications(), vol 58. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0857-4_14

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