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The good, the bad, and the random: an eye-tracking study of ad quality in web search

Published:19 July 2010Publication History

ABSTRACT

We investigate how people interact with Web search engine result pages using eye-tracking. While previous research has focused on the visual attention devoted to the 10 organic search results, this paper examines other components of contemporary search engines, such as ads and related searches. We systematically varied the type of task (informational or navigational), the quality of the ads (relevant or irrelevant to the query), and the sequence in which ads of different quality were presented. We measured the effects of these variables on the distribution of visual attention and on task performance. Our results show significant effects of each variable. The amount of visual attention that people devote to organic results depends on both task type and ad quality. The amount of visual attention that people devote to ads depends on their quality, but not the type of task. Interestingly, the sequence and predictability of ad quality is also an important factor in determining how much people attend to ads. When the quality of ads varied randomly from task to task, people paid little attention to the ads, even when they were good. These results further our understanding of how attention devoted to search results is influenced by other page elements, and how previous search experiences influence how people attend to the current page.

References

  1. Aula, A., Majaranta, P. & Räihä, K. Eye-tracking reveals the personal styles for search result evaluation. In Proceedings INTERACT 2005, 1058--1061. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Broder, A. A taxonomy of web search. SIGIR Forum, 2002, vol. 36, 3--10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Beymer, D., Russell, D. & Orton, P. Z. An eye tracking study of how font size, font type, and pictures influence online reading. In Proceedings INTERACT 2007, 456--460. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Buscher, G., Cutrell, E. & Morris, M. R. What do you see when you're surfing? Using eye tracking to predict salient regions of web pages. In Proceedings CHI 2009, 21--30. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Clarke, C. L. A.,, Agichtein, E.., Dumais, S. & White, R. W. The influence of caption features on clickthrough patterns in web search. In Proceedings SIGIR 2007, 135--142. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Cutrell, E. & Guan, Z. What are you looking for? An eye-tracking study of information usage in web search. In Proceedings CHI 2007, 407--416. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Downey, D., Dumais, S., Liebling, D. & Horvitz, E. Understanding the relationship between searchers' queries and information goals. In Proceedings CIKM 2008, 449--458. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Fallows, D. Search engine users. Pew Research Center, 2005. Retrieved January 18, 2010 from http//www.pewinternet.org/Reports/2005/Search-Engine-Users.aspx.Google ScholarGoogle Scholar
  9. Granka, L. A., Joachims, T. & Gay, G. Eye-tracking analysis of user behavior in WWW search. In Proceedings SIGIR 2004, 478--479. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Guan, Z. & Cutrell, E. An eye tracking study of the effect of target rank on web search. In Proceedings CHI 2007, 417--420. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Höchstötter, N. & Lewandowski, D. What users see - Structures in search engine results pages. Information Sciences, 2009, vol. 179, 1796--1812. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Hotchkiss, G., Alston, S. & Edwards, G. Eye tracking study, 2006. Retrieved January 18, 2010 from http//www.enquiro.com/eyetrackingreport.asp.Google ScholarGoogle Scholar
  13. Jansen, B. J. The comparative effectiveness of sponsored and nonsponsored links for Web e-commerce queries. ACM Transactions on the Web, 2007, vol. 1, article 3. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Jansen, B. J., Brown, A. & Resnick, M. Factors relating to the decision to click on a sponsored link. Decision Support Systems, 2007, vol. 44, 46--59. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Jansen, B. J. & Spink, A. Investigating customer click through behaviour with integrated sponsored and nonsponsored results. International Journal of Internet Marketing and Advertising, 2009, vol. 5, 74--94.Google ScholarGoogle ScholarCross RefCross Ref
  16. Joachims, T., Granka, L., Pan, B., Hembrooke, H. & Gay, G. Accurately interpreting clickthrough data as implicit feedback. In Proceedings SIGIR 2005, 154--161. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Lorigo, L., Haridasan, M., Brynjarsdóttir, H., Xia, L., Joachims, T., Gay, G., Granka, L., Pellacini, F. & Pan, B. Eye tracking and online search Lessons learned and challenges ahead. JASIST, 2008, vol. 59, 1041--1052. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Nielsen, J. F-Shaped pattern for reading Web content, 2006. Retrieved January 18, 2010 from http//www.useit.com/alertbox/reading_pattern.html.Google ScholarGoogle Scholar
  19. Pan, B., Hembrooke, H., Joachims, T., Lorigo, L., Gay, G. & Granka, L. In Google we trust: Users' decisions on rank, position, and relevance. Journal of Computer-Mediated Communication, 2007, vol. 12, 801--823.Google ScholarGoogle ScholarCross RefCross Ref
  20. Rose, D. E. & Levinson, D. Understanding user goals in web search. In Proceedings WWW 2004, 13--19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Smith, C. L. & Kantor, P. B. User adaptation: Good results from poor systems. In Proceedings SIGIR 2008, 147--154. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Turpin, A. & Schöler, F. User performance versus precision measures for simple search tasks. In Proceedings of SIGIR 2006, 11--18. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. White, R. W., Dumais, S.T. & Teevan, J. Characterizing the influence of domain expertise on Web search. In Proceedings of WSDM 2009, 132--141. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. White, R. W. & Morris, D. Investigating the querying and browsing behavior of advanced search engine users. In Proceedings of SIGIR 2007, 255--262. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Yan, J., Liu, N., Wang, G., Zhang, W., Jiang, Y. & Chen, Z. How much can behavioral targeting help online advertising? In Proceedings WWW 2009, 261--270. Google ScholarGoogle ScholarDigital LibraryDigital Library

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      • Published in

        cover image ACM Conferences
        SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
        July 2010
        944 pages
        ISBN:9781450301534
        DOI:10.1145/1835449

        Copyright © 2010 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 19 July 2010

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        SIGIR '10 Paper Acceptance Rate87of520submissions,17%Overall Acceptance Rate792of3,983submissions,20%

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