Proceedings of the 12th ACM Conference on Electronic Commerce 2011
DOI: 10.1145/1993574.1993577
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Optimal auctions with positive network externalities

Abstract: We consider the problem of designing auctions in social networks for goods that exhibit single-parameter submodular network externalities in which a bidder's value for an outcome is a fixed private type times a known submodular function of the allocation of his friends. Externalities pose many issues that are hard to address with traditional techniques; our work shows how to resolve these issues in a specific setting of particular interest. We operate in a Bayesian environment and so assume private values are … Show more

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Cited by 38 publications
(28 citation statements)
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“…In addition, Haghpanah et al (2013) studied positive externalities in the design of auctions. They proved that the optimal auction problem is APX-hard and proposed a type of fixed approximation algorithm for a special case of externalities in step functions such that total revenue is maximized.…”
Section: Revenue/profit Maximizationmentioning
confidence: 99%
“…In addition, Haghpanah et al (2013) studied positive externalities in the design of auctions. They proved that the optimal auction problem is APX-hard and proposed a type of fixed approximation algorithm for a special case of externalities in step functions such that total revenue is maximized.…”
Section: Revenue/profit Maximizationmentioning
confidence: 99%
“…Externalities in online advertising were investigated by [GM08] using a probabilistic model. CA with externalities were presented in [KMSW10,CS12,HIMM13], and maximizing social welfare was shown to be NP-hard. In [GS10] a sponsored search setting was treated where each advertiser has two valuations, one if his ad is shown exclusively and one if it is shown together with other ads.…”
Section: Related Workmentioning
confidence: 99%
“…These models are substantially different from Adaptive Seeding, as the entire set of possible seeds is available at every stage and the optimization is only over their influence. Hartline et al [22] and Haghpanah et al [23] consider revenue maximization of digital goods where the individual's valuation of an item is a function of its adoption by her neighbors. Adaptive Seeding is similar in that seeding neighbors during the second stage depends on having their neighbors seeded as well.…”
Section: E Related Workmentioning
confidence: 99%