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Extracting accurate and complete results from search engines: Case study windows live

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  • Mike Thelwall

Abstract

Although designed for general Web searching, Webometrics and related research commercial search engines are also used to produce estimated hit counts or lists of URLs matching a query. Unfortunately, however, they do not return all matching URLs for a search and their hit count estimates are unreliable. In this article, we assess whether it is possible to obtain complete lists of matching URLs from Windows Live, and whether any of its hit count estimates are robust. As part of this, we introduce two new methods to extract extra URLs from search engines: automated query splitting and automated domain and TLD searching. Both methods successfully identify additional matching URLs but the findings suggest that there is no way to get complete lists of matching URLs or accurate hit counts from Windows Live, although some estimating suggestions are provided.

Suggested Citation

  • Mike Thelwall, 2008. "Extracting accurate and complete results from search engines: Case study windows live," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(1), pages 38-50, January.
    • Handle: RePEc:bla:jamist:v:59:y:2008:i:1:p:38-50
    DOI: 10.1002/asi.20704
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    Cited by:

    1. Enrique Orduña-Malea & John J. Regazzi, 2014. "U.S. academic libraries: understanding their web presence and their relationship with economic indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 315-336, January.
    2. Han Park, 2012. "How do social scientists use link data from search engines to understand Internet-based political and electoral communication?," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(2), pages 679-693, February.
    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.
    4. David Wilkinson & Pardeep Sud & Mike Thelwall, 2014. "Substance without citation: evaluating the online impact of grey literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 797-806, February.
    5. Han Woo Park & Jungwon Yoon & Loet Leydesdorff, 2016. "The normalization of co-authorship networks in the bibliometric evaluation: the government stimulation programs of China and Korea," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1017-1036, November.
    6. Pardeep Sud & Mike Thelwall, 2014. "Linked title mentions: a new automated link search candidate," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1831-1849, December.
    7. Vaughan, Liwen & You, Justin, 2010. "Word co-occurrences on Webpages as a measure of the relatedness of organizations: A new Webometrics concept," Journal of Informetrics, Elsevier, vol. 4(4), pages 483-491.

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