Truthful approximation mechanisms for restricted combinatorial auctions: extended abstract
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One of the most important innovations of social networking websites is the notion of a "feed", a sequence of news items presented to the user as a stream that expands as the user scrolls down. The common method for monetizing such streams is to insert ads in between news items. In this paper, we model this setting, and observe that allocation and pricing of ad insertions in a stream poses interesting algorithmic and mechanism design challenges. In particular, we formulate an optimization problem that captures a typical stream ad placement setting. We give an approximation algorithm for this problem that provably achieves a value close to the optimal, and show how this algorithm can be turned into an incentive compatible mechanism. Finally, we conclude with a simple practical algorithm that makes the allocation decisions in an online fashion. We prove this algorithm to be approximately welfare-maximizing and show that it also has good incentive properties.