A Structural Model of Sponsored Search Advertising Auctions

155 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads (2019, methodology): “The quality score is the outcome of a predictive method that measures the likelihood a user will click on any particular ad (Athey and Nekipelov 2010), thus adjusting for the relative merit of a bid for the advertising platform.”
Understanding the paradigm shift to computational social science in the presence of big data (2014, unknown): “formats and modified competitive environments on keyword auctions [7].”
Efficient Ranking in Sponsored Search (2011, background): “While separability is only an approximation to actual CTR patterns [2], it is still relevant for the search engine to estimate position-normalized advertiser effects because wi = μi is a natural choice for the quality score.”
Algorithmic bias? An empirical study into apparent gender-based discrimination in the display of STEM career ads (2019, methodology): “The quality score is the outcome of a predictive method that measures the likelihood a user will click on any particular ad (Athey and Nekipelov, 2010), thus adjusting for the relative merit of a bid for the advertising platform.”
LBS Research Online (2021, unknown): “The quality score is the outcome of a predictive method that measures the likelihood a user will click on any particular ad (Athey and Nekipelov, 2010), thus adjusting for the relative merit of a bid for the advertising platform.”