Abstract
We study the use of viral marketing strategies on social networks that seek to maximize revenue from the sale of a single product. We propose a model in which the decision of a buyer to buy the product is influenced by friends that own the product and the price at which the product is offered. The influence model we analyze is quite general, naturally extending both the Linear Threshold model and the Independent Cascade model, while also incorporating price information. We consider sales proceeding in a cascading manner through the network, i.e. a buyer is offered the product via recommendations from its neighbors who own the product. In this setting, the seller influences events by offering a cashback to recommenders and by setting prices (via coupons or discounts) for each buyer in the social network. This choice of prices for the buyers is termed as the seller’s strategy.
Finding a seller strategy which maximizes the expected revenue in this setting turns out to be NP-hard. However, we propose a seller strategy that generates revenue guaranteed to be within a constant factor of the optimal strategy in a wide variety of models. The strategy is based on an influence-and-exploit idea, and it consists of finding the right trade-off at each time step between: generating revenue from the current user versus offering the product for free and using the influence generated from this sale later in the process.
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Arthur, D., Motwani, R., Sharma, A., Xu, Y.: Pricing strategies for viral marketing on social networks (2009), http://arxiv.org/abs/0902.3485
Arthur, D., Vassilvitskii, S.: k-means++: the advantages of careful seeding. In: SODA 2007: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, Philadelphia, PA, USA, pp. 1027–1035. Society for Industrial and Applied Mathematics (2007)
Domingos, P., Richardson, M.: Mining the network value of customers. In: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 57–66 (2001)
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. WH Freeman & Co., New York (1979)
Hartline, J., Mirrokni, V., Sundararajan, M.: Optimal Marketing Strategies over Social Networks. In: Proceedings of the 17th international conference on World Wide Web (2008)
Kempe, D., Kleinberg, J., Tardos, É.: Maximizing the spread of influence through a social network. In: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 137–146 (2003)
Kleinberg, J.: Cascading Behavior in Networks: Algorithmic and Economic Issues. In: Nisan, N., Roughgarden, T., Tardos, E., Vazirani, V.V. (eds.) Algorithmic Game Theory. Cambridge University Press, New York (2007)
Kleitman, D.J., West, D.B.: Spanning Trees with Many Leaves. SIAM Journal on Discrete Mathematics 4, 99 (1991)
Leskovec, J., Singh, A., Kleinberg, J.: Patterns of influence in a recommendation network. In: Ng, W.-K., Kitsuregawa, M., Li, J., Chang, K. (eds.) PAKDD 2006. LNCS (LNAI), vol. 3918, pp. 380–389. Springer, Heidelberg (2006)
Leskovec, J., Adamic, L.A., Huberman, B.A.: The dynamics of viral marketing. ACM Trans. Web 1(1), 5 (2007)
Lu, H.I., Ravi, R.: Approximating Maximum Leaf Spanning Trees in Almost Linear Time. Journal of Algorithms 29(1), 132–141 (1998)
BBC News. Facebook valued at $15 billion (2007), http://news.bbc.co.uk/2/hi/business/7061042.stm
Schonfeld, E.: Amiando makes tickets go viral and widgetizes event management (2008), http://www.techcrunch.com/2008/07/17/amiando-makes-tickets-go-viral-and-widgetizes-event-management-200-discount-for-techcrunch-readers/
Solis-Oba, R.: 2-Approximation Algorithm for finding a Spanning Tree with Maximum Number of leaves. In: Proceedings of the Sixth European Symposium on Algorithms, pp. 441–452 (1998)
Wikipedia. Facebook revenue in 2008 (2008), http://en.wikipedia.org/wiki/Facebook
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Arthur, D., Motwani, R., Sharma, A., Xu, Y. (2009). Pricing Strategies for Viral Marketing on Social Networks. In: Leonardi, S. (eds) Internet and Network Economics. WINE 2009. Lecture Notes in Computer Science, vol 5929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10841-9_11
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DOI: https://doi.org/10.1007/978-3-642-10841-9_11
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