TY - GEN
T1 - The complex dynamics of sponsored search markets
AU - Robu, Valentin
AU - La Poutré, Han
AU - Bohte, Sander
PY - 2009
Y1 - 2009
N2 - This paper provides a comprehensive study of the structure and dynamics of online advertising markets, mostly based on techniques from the emergent discipline of complex systems analysis. First, we look at how the display rank of a URL link influences its click frequency, for both sponsored search and organic search. Second, we study the market structure that emerges from these queries, especially the market share distribution of different advertisers. We show that the sponsored search market is highly concentrated, with less than 5% of all advertisers receiving over 2/3 of the clicks in the market. Furthermore, we show that both the number of ad impressions and the number of clicks follow power law distributions of approximately the same coefficient. However, we find this result does not hold when studying the same distribution of clicks per rank position, which shows considerable variance, most likely due to the way advertisers divide their budget on different keywords. Finally, we turn our attention to how such sponsored search data could be used to provide decision support tools for bidding for combinations of keywords. We provide a method to visualize keywords of interest in graphical form, as well as a method to partition these graphs to obtain desirable subsets of search terms.
AB - This paper provides a comprehensive study of the structure and dynamics of online advertising markets, mostly based on techniques from the emergent discipline of complex systems analysis. First, we look at how the display rank of a URL link influences its click frequency, for both sponsored search and organic search. Second, we study the market structure that emerges from these queries, especially the market share distribution of different advertisers. We show that the sponsored search market is highly concentrated, with less than 5% of all advertisers receiving over 2/3 of the clicks in the market. Furthermore, we show that both the number of ad impressions and the number of clicks follow power law distributions of approximately the same coefficient. However, we find this result does not hold when studying the same distribution of clicks per rank position, which shows considerable variance, most likely due to the way advertisers divide their budget on different keywords. Finally, we turn our attention to how such sponsored search data could be used to provide decision support tools for bidding for combinations of keywords. We provide a method to visualize keywords of interest in graphical form, as well as a method to partition these graphs to obtain desirable subsets of search terms.
KW - Collaborative filtering
KW - Community detection
KW - Complex systems
KW - Keyword advertising
KW - Power laws
KW - Sponsored search
UR - http://www.scopus.com/inward/record.url?scp=69949181234&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-03603-3_14
DO - 10.1007/978-3-642-03603-3_14
M3 - Conference contribution
AN - SCOPUS:69949181234
SN - 3642036023
SN - 9783642036026
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 183
EP - 198
BT - Agents and Data Mining Interaction - 4th International Workshop, ADMI 2009, Revised Selected Papers
T2 - 4th International Workshop on Agents and Data Mining Interaction, ADMI 2009
Y2 - 10 May 2009 through 15 May 2009
ER -