Abstract
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.
This work was performed based on a Microft Research “Beyond Search” award. The authors wish to thank Microsoft Research for their support.
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References
Baldassarri, A., Barrat, A., Cappocci, A., Halpin, H., Lehner, U., Ramasco, J., Robu, V., Taraborelli, D.: The berners-lee hypothesis: Power laws and group structure in flickr, 2008. In: Proc. of Dagstuhl Seminar on Social Web Communities, Dagstuhl DROPS 08391 (2008)
Bar-Yam, Y.: The dynamics of complex systems. Westview Press (2003)
Batagelj, V., Mrvar, A.: Pajek - A program for large network analysis. Connections 21, 47–57 (1998)
Bohte, S.M., Gerding, E., Poutré, J.L.: Market-based recommendation: Agents that compete for consumer attention. ACM Trans. Internet Technology 4(4), 420–448 (2004)
Borgs, C., Chayes, J., Immorlica, N., Jain, K., Etesami, O., Mahdian, M.: Dynamics of bid optimization in online advertisement auctions. In: WWW 2007: Proc. 16th Int. Conf. World Wide Web, pp. 531–540. ACM Press, New York (2007)
Carter, T.: A short trip through entropy to power laws, 2007. In: Complex Systems Summer School, Santa Fe Institute, NM (2007)
Cilibrasi, R.L., Vitanyi, P.M.B.: The google similarity distance. IEEE Trans. on Knowl. and Data Eng. 19(3), 370–383 (2007)
Craswell, N., Zoeter, O., Taylor, M., Ramsey, B.: An experimental comparison of click position-bias models. In: Proc of WSDM 2008, pp. 87–94. ACM Press, New York (2008)
Ghose, A., Yang, S.: Analyzing search engine advertising: firm behavior and cross-selling in electronic markets. In: WWW 2008: Proc. of the 17th Int. Conf. on World Wide Web, pp. 219–226. ACM Press, New York (2008)
Halpin, H., Robu, V., Shepherd, H.: The dynamics and semantics of collaborative tagging. In: Proc. of the 1st Semantic Authoring and Annotation Workshop (SAAW 2006) (2006)
Halpin, H., Robu, V., Shepherd, H.: The complex dynamics of collaborative tagging. In: Proc. 16th Int. World Wide Web Conference (WWW 2007), pp. 211–220. ACM, New York (2007)
Jin, R.K.-X., Parkes, D.C., Wolfe, P.J.: Analysis of bidding networks in eBay: Aggregate preference identification through community detection. In: Proc. AAAI Workshop on Plan, Activity and Intent Recognition (2007)
Juda, A.I., Parkes, D.C.: An options-based method to solve the composability problem in sequential auctions. In: Faratin, P., Rodríguez-Aguilar, J.-A. (eds.) AMEC 2004. LNCS (LNAI), vol. 3435, pp. 44–58. Springer, Heidelberg (2005)
Juda, A.I., Parkes, D.C.: The sequential auction problem on ebay: An empirical analysis and a solution. In: Proc. 7th ACM Conf. on Electr. Commerce, pp. 180–189. ACM Press, New York (2006)
Judd, K.L., Tesfatsion, L.: Handbook of computational economics II: Agent-Based computational economics. Handbooks in Economics Series. North-Holland, The Netherlands (2005)
Linden, G., Smith, B., York, J.: Amazon.com recommendations: item-to-item collaborative filtering. IEEE Internet Computing 7(1), 76–80 (2003)
Mous, L., Robu, V., La Poutré, H.: Can priced options solve the exposure problem in sequential auctions? ACM SIGEcom Exchanges 7(2) (2008)
Mous, L., Robu, V., La Poutré, H.: Using priced options to solve the exposure problem in sequential auctions. In: Agent-Mediated Electronic Commerce (AMEC 2008). LNCS (LNAI). Springer, Heidelberg (2008) (to appear)
Newman, M.: Power laws, pareto distributions and zipf’s law. Contemporary Physics 46, 323–351 (2005)
Newman, M.E.J.: Fast algorithm for detecting community structure in networks. Phys. Rev. E 69, 66–133 (2004)
Robu, V., La Poutré, H.: Designing bidding strategies in sequential auctions for risk averse agents. In: Agent-Mediated Electronic Commerce. LNBIP, vol. 13, pp. 76–89. Springer, Heidelberg (2007)
Robu, V., Poutré, H.L.: Learning the structure of utility graphs used in multi-issue negotiation through collaborative filtering. In: Proc. of the Pacific Rim Workshop on Multi-Agent Systems (PRIMA 2005) (2005)
Robu, V., Somefun, D., Poutré, J.A.L.: Modeling complex multi-issue negotiations using utility graphs. In: Proc. of the 4th Int. Conf. on Autonomous Agents & Multi Agent Systems (AAMAS), Utrecht, The Netherlands, pp. 280–287. ACM Press, New York (2005)
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Robu, V., La Poutré, H., Bohte, S. (2009). The Complex Dynamics of Sponsored Search Markets. In: Cao, L., Gorodetsky, V., Liu, J., Weiss, G., Yu, P.S. (eds) Agents and Data Mining Interaction. ADMI 2009. Lecture Notes in Computer Science(), vol 5680. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03603-3_14
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DOI: https://doi.org/10.1007/978-3-642-03603-3_14
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