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A Dynamics for Advertising on Networks

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Web and Internet Economics (WINE 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10660))

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Abstract

We study the following question facing businesses in the world of online advertising: how should an advertising budget be spent when there are competing products? Broadly, there are two primary modes of advertising: (i) the equivalent of billboards in the real-world and (search or display) ads online that convert a percentage of the population that sees them, and (ii) social campaigns where the goal is to select a set of initial adopters who influence others to buy via their social network. Prior work towards the above question has largely focused on developing models to understand the effect of one mode or the other. We present a stochastic dynamics to model advertising in social networks that allows both and incorporates the three primary forces at work in such advertising campaigns: (1) the type of campaign – which can combine buying ads and seed selection, (2) the topology of the social network, and (3) the relative quality of the competing products. This model allows us to study the evolution of market share of multiple products with different qualities competing for the same set of users, and the effect that different advertising campaigns can have on the market share. We present theoretical results to understand the long-term behavior of the parameters on the market share and complement them with empirical results that give us insights about the, harder to mathematically understand, short-term behavior of the model.

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Notes

  1. 1.

    We can think of one products as the “null” choice – i.e., no product is selected.

  2. 2.

    For example, for products such as cars, time steps may be on the order of years. Hence, we may be interested in a constant number of time steps, which is less than the fastest mixing time we could hope for.

  3. 3.

    The choice of parameters is inspired by the parameters we get when a fitting our model to real world datasets; see the full version of the paper.

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Author information

Authors and Affiliations

  1. École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

    L. Elisa Celis & Nisheeth K. Vishnoi

  2. Massachusetts Institute of Technology (MIT), Cambridge, USA

    Mina Dalirrooyfard

Authors
  1. L. Elisa Celis
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  2. Mina Dalirrooyfard
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  3. Nisheeth K. Vishnoi
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Corresponding author

Correspondence to L. Elisa Celis .

Editor information

Editors and Affiliations

  1. Microsoft Research, Redmond, Washington, USA

    Nikhil R. Devanur

  2. Shanghai University of Finance and Economics, Shanghai, China

    Pinyan Lu

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Celis, L.E., Dalirrooyfard, M., Vishnoi, N.K. (2017). A Dynamics for Advertising on Networks. In: R. Devanur, N., Lu, P. (eds) Web and Internet Economics. WINE 2017. Lecture Notes in Computer Science(), vol 10660. Springer, Cham. https://doi.org/10.1007/978-3-319-71924-5_7

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  • DOI: https://doi.org/10.1007/978-3-319-71924-5_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71923-8

  • Online ISBN: 978-3-319-71924-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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