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

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Estimating search engine index size is crucial for understanding web accessibility. Our novel method reveals dramatic fluctuations in Google and Bing

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Area of Science:

  • Web Science and Information Retrieval
  • Computational Social Science
  • Webometrics

Background:

  • Search engine index size is a key metric for web search engine quality and accessibility.
  • Previous estimates of indexed web size have been largely one-off, lacking longitudinal perspective.
  • Understanding the scale of the World Wide Web (WWW) accessible to users is essential.

Purpose of the Study:

  • To propose and validate a novel method for estimating the size of web search engine indices.
  • To provide a longitudinal analysis of Google and Bing's index sizes over a nine-year period (2006-2015).
  • To investigate the reliability of web search engines for webometric studies.

Main Methods:

  • Developed a novel estimation technique based on extrapolating document frequencies of words from a large static web page corpus.
  • Collected and analyzed data on Google and Bing's index sizes from March 2006 to January 2015.
  • Compared longitudinal index size estimates with known changes in search engine infrastructure.

Main Results:

  • Index size estimates for Google and Bing varied dramatically over the nine-year study period.
  • Google generally maintained a larger index size compared to Bing.
  • Observed variability in index size is largely attributable to changes in search engine indexing and ranking infrastructure.

Conclusions:

  • The proposed method offers a new approach to estimating search engine index size.
  • Dramatic temporal variations in index size challenge the reliability of previous one-off webometric estimates.
  • Web search engines may not be suitable for reliable cross-sectional webometric studies due to dynamic index changes.