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Searching the web: The public and their queries

Author

Listed:
  • Amanda Spink
  • Dietmar Wolfram
  • Major B. J. Jansen
  • Tefko Saracevic

Abstract

In studying actual Web searching by the public at large, we analyzed over one million Web queries by users of the Excite search engine. We found that most people use few search terms, few modified queries, view few Web pages, and rarely use advanced search features. A small number of search terms are used with high frequency, and a great many terms are unique; the language of Web queries is distinctive. Queries about recreation and entertainment rank highest. Findings are compared to data from two other large studies of Web queries. This study provides an insight into the public practices and choices in Web searching.

Suggested Citation

  • Amanda Spink & Dietmar Wolfram & Major B. J. Jansen & Tefko Saracevic, 2001. "Searching the web: The public and their queries," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 52(3), pages 226-234.
    • Handle: RePEc:bla:jamist:v:52:y:2001:i:3:p:226-234
    DOI: 10.1002/1097-4571(2000)9999:99993.0.CO;2-R
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    Cited by:

    1. Jia Liu & Olivier Toubia, 2020. "Search query formation by strategic consumers," Quantitative Marketing and Economics (QME), Springer, vol. 18(2), pages 155-194, June.
    2. Kevin Wong & Geoff Walton & Gavin Bailey, 2021. "Using information science to enhance educational preventing violent extremism programs," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(3), pages 362-376, March.
    3. Cédric Argenton & Jens Prüfer, 2012. "Search Engine Competition With Network Externalities," Journal of Competition Law and Economics, Oxford University Press, vol. 8(1), pages 73-105.
    4. Claudia Diamantini & Paolo Lo Giudice & Domenico Potena & Emanuele Storti & Domenico Ursino, 2021. "An Approach to Extracting Topic-guided Views from the Sources of a Data Lake," Information Systems Frontiers, Springer, vol. 23(1), pages 243-262, February.
    5. Claudia Diamantini & Paolo Lo Giudice & Domenico Potena & Emanuele Storti & Domenico Ursino, 0. "An Approach to Extracting Topic-guided Views from the Sources of a Data Lake," Information Systems Frontiers, Springer, vol. 0, pages 1-20.
    6. Baojun Ma & Qiang Wei & Guoqing Chen & Jin Zhang & Xunhua Guo, 2017. "Content and Structure Coverage: Extracting a Diverse Information Subset," INFORMS Journal on Computing, INFORMS, vol. 29(4), pages 660-675, November.
    7. Veda C. Storey & Andrew Burton-Jones & Vijayan Sugumaran & Sandeep Purao, 2008. "CONQUER: A Methodology for Context-Aware Query Processing on the World Wide Web," Information Systems Research, INFORMS, vol. 19(1), pages 3-25, March.
    8. Sinziana Spiridon, 2010. "Patterns In Query Reformulation In Online Searching Behavior," Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 2010, pages 407-416, july.
    9. Huseyin C. Ozmutlu, 2009. "Markovian analysis for automatic new topic identification in search engine transaction logs," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(6), pages 737-768, November.

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