Book contents
- Frontmatter
- Contents
- Foreword
- Preface
- Contributors
- I Computing in Games
- II Algorithmic Mechanism Design
- III Quantifying the Inefficiency of Equilibria
- IV Additional Topics
- 22 Incentives and Pricing in Communications Networks
- 23 Incentives in Peer-to-Peer Systems
- 24 Cascading Behavior in Networks: Algorithmic and Economic Issues
- 25 Incentives and Information Security
- 26 Computational Aspects of Prediction Markets
- 27 Manipulation-Resistant Reputation Systems
- 28 Sponsored Search Auctions
- 29 Computational Evolutionary Game Theory
- Index
28 - Sponsored Search Auctions
from IV - Additional Topics
Published online by Cambridge University Press: 31 January 2011
- Frontmatter
- Contents
- Foreword
- Preface
- Contributors
- I Computing in Games
- II Algorithmic Mechanism Design
- III Quantifying the Inefficiency of Equilibria
- IV Additional Topics
- 22 Incentives and Pricing in Communications Networks
- 23 Incentives in Peer-to-Peer Systems
- 24 Cascading Behavior in Networks: Algorithmic and Economic Issues
- 25 Incentives and Information Security
- 26 Computational Aspects of Prediction Markets
- 27 Manipulation-Resistant Reputation Systems
- 28 Sponsored Search Auctions
- 29 Computational Evolutionary Game Theory
- Index
Summary
Abstract
One of the more visible means by which the Internet has disrupted traditional activity is the manner in which advertising is sold. Offline, the price for advertising is typically set by negotiation or posted price. Online, much advertising is sold via auction. Most prominently, Web search engines like Google and Yahoo! auction space next to search results, a practice known as sponsored search. This chapter describes the auctions used and how the theory developed in earlier chapters of this book can shed light on their properties. We close with a brief discussion of unresolved issues associated with the sale of advertising on the Internet.
Introduction
Web search engines like Google and Yahoo! monetize their service by auctioning off advertising space next to their standard algorithmic search results. For example, Apple or Best Buy may bid to appear among the advertisements – usually located above or to the right of the algorithmic results – whenever users search for “ipod.” These sponsored results are displayed in a format similar to algorithmic results: as a list of items each containing a title, a text description, and a hyperlink to the advertiser's Web page. We call each position in the list a slot. Generally, advertisements that appear in a higher ranked slot (higher on the page) garner more attention and more clicks from users. Thus, all else being equal, merchants generally prefer higher ranked slots to lower ranked slots.
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- Chapter
- Information
- Algorithmic Game Theory , pp. 699 - 716Publisher: Cambridge University PressPrint publication year: 2007
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