Abstract
We present a characterization of empirical price data from sponsored search auctions. We show that simple models drawing bid values independently from a fixed distribution can be tuned to match empirical data on average, but still fail to account for deviations observed in individual auctions. Hypothesizing that these deviations are due to strategic bidding, we define measures of “jamming” behavior and show that actual auctions exhibit significantly more jamming than predicted by such models. Correspondingly, removing the jamming bids from observed auction data yields a much closer fit. We demonstrate that this characterization is a revealing tool for analysis, using model parameter values and measures of jamming to summarize the effects of query modifers on a set of keyword auctions.
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© 2007 Springer-Verlag Berlin Heidelberg
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Ganchev, K., Kulesza, A., Tan, J., Gabbard, R., Liu, Q., Kearns, M. (2007). Empirical Price Modeling for Sponsored Search. In: Deng, X., Graham, F.C. (eds) Internet and Network Economics. WINE 2007. Lecture Notes in Computer Science, vol 4858. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77105-0_58
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DOI: https://doi.org/10.1007/978-3-540-77105-0_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77104-3
Online ISBN: 978-3-540-77105-0
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