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Estimating search engine index size variability: a 9-year longitudinal study

Author

Listed:
  • Antal Bosch

    (Radboud University)

  • Toine Bogers

    (Aalborg University Copenhagen)

  • Maurice Kunder

    (De Kunder Internet Media)

Abstract

One of the determining factors of the quality of Web search engines is the size of their index. In addition to its influence on search result quality, the size of the indexed Web can also tell us something about which parts of the WWW are directly accessible to the everyday user. We propose a novel method of estimating the size of a Web search engine’s index by extrapolating from document frequencies of words observed in a large static corpus of Web pages. In addition, we provide a unique longitudinal perspective on the size of Google and Bing’s indices over a nine-year period, from March 2006 until January 2015. We find that index size estimates of these two search engines tend to vary dramatically over time, with Google generally possessing a larger index than Bing. This result raises doubts about the reliability of previous one-off estimates of the size of the indexed Web. We find that much, if not all of this variability can be explained by changes in the indexing and ranking infrastructure of Google and Bing. This casts further doubt on whether Web search engines can be used reliably for cross-sectional webometric studies.

Suggested Citation

  • Antal Bosch & Toine Bogers & Maurice Kunder, 2016. "Estimating search engine index size variability: a 9-year longitudinal study," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 839-856, May.
    • Handle: RePEc:spr:scient:v:107:y:2016:i:2:d:10.1007_s11192-016-1863-z
    DOI: 10.1007/s11192-016-1863-z
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    References listed on IDEAS

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    1. Steve Lawrence & C. Lee Giles, 1999. "Accessibility of information on the web," Nature, Nature, vol. 400(6740), pages 107-107, July.
    2. Mike Thelwall, 2008. "Quantitative comparisons of search engine results," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(11), pages 1702-1710, September.
    3. Thelwall, Mike & Sud, Pardeep, 2012. "Webometric research with the Bing Search API 2.0," Journal of Informetrics, Elsevier, vol. 6(1), pages 44-52.
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    Cited by:

    1. M. E. Bontempi & M. Frigeri & R. Golinelli & M. Squadrani, 2019. "Uncertainty, Perception and the Internet," Working Papers wp1134, Dipartimento Scienze Economiche, Universita' di Bologna.
    2. Isidro F. Aguillo, 2020. "Altmetrics of the Open Access Institutional Repositories: a webometrics approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(3), pages 1181-1192, June.
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    4. Enrique Orduña-Malea & Cristina I. Font-Julián & Jorge Serrano-Cobos, 2024. "Open access publications drive few visits from Google Search results to institutional repositories," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7131-7152, November.

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