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Foraging patterns in online searches.

Xiangwen Wang1,2,3, Michel Pleimling1,2,4

  • 1Department of Physics, Virginia Tech, Blacksburg, Virginia 24061-0435, USA.

Physical Review. E
|April 19, 2017
PubMed
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Online searches are analyzed as foraging processes. Modern search engines improve efficiency, leading users to find information through local exploration rather than broad page-hopping.

Area of Science:

  • Information Science
  • Computational Social Science
  • Search Engine Optimization

Background:

  • Online searches are a primary method of information gathering, generating billions of daily clicks.
  • Understanding user search behavior is crucial for search engine efficiency and design.

Purpose of the Study:

  • To analyze online search behavior using foraging theory.
  • To evaluate search engine efficiency by examining user click patterns over time.

Main Methods:

  • Analysis of three large-scale click-through logs containing millions of search queries.
  • Application of foraging theory metrics: probability distributions, complementary cumulative distribution functions, mean square displacements, and entropies.

Main Results:

Related Experiment Videos

  • Click logs reveal distinct search patterns over time, indicating increased search engine efficiency.
  • Older logs show a combination of local searches and power-law distributed relocation phases.
  • Newer logs demonstrate a shift towards predominantly local searches, with fewer relocation phases.

Conclusions:

  • Modern search engines facilitate efficient information retrieval through local exploration of search results pages.
  • Search engine quality correlates with the degree to which users can find information locally, minimizing the need for broader, intermittent exploration.