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Advertisement Allocation and Mechanism Design in Native Stream Advertising

  • Iftah Gamzu
  • Iordanis Koutsopoulos
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 813)

Abstract

We study optimal advertisement allocation in native stream advertising, which exhibits notable fundamental differences from traditional web advertising. Our model highlights the influence of distance between consecutively projected ads on user engagement, which implies interesting negative externalities between ads: when there are fewer intervening posts between two ads, there is higher ad fatigue and lower user engagement. We study the problem of advertisement selection and placement in a stream so as to maximize social welfare. We fully characterize the computational complexity of the problem by demonstrating that it is tightly connected to a special form of interval scheduling. Next, we prove that it is strictly NP-hard (SNP-hard) but can be efficiently approximated to within 1 / 2 of the optimum. We complement this result by studying the mechanism design variant of the problem and develop a 1 / 2-approximation truthful-in-expectation mechanism. We also consider mechanisms that guarantee a stronger deterministic form of truthfulness. We believe that these results lay a valuable theoretical foundation for further research in the field.

Keywords

Native advertising Mechanism design Ad placement Algorithms 

Notes

Acknowledgments

I. Koutsopoulos acknowledges the support of the project “Research Reinforcement” by the General Secretariat for Research and Technology (GSRT).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Amazon ResearchHaifaIsrael
  2. 2.Department of InformaticsAthens University of Economics and BusinessAthensGreece

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