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Relevance in Web search: between content, authority and popularity

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  • Anton Oleinik

    (Memorial University of Newfoundland St. John’s
    Central Economics and Mathematics Institute of the Russian Academy of Sciences)

Abstract

The algorithms underpinning information retrieval shape its outcomes and have epistemological, social and political consequences. On the one hand, the Web search algorithms place a specific actor—the Web librarian (cataloguer), the document’s creator, the expert (“authority”), the user or the service provider (developer and operator of a search engine)—in the position of a decision-maker. Each of them has distinctive criteria of relevance in information retrieval. On the other hand, the application of those criteria determines what information the user receives. Content-based search places emphasis on the contents of retrievable documents whereas collaborative search shifts the focus of attention to opinions of experts and other users. The outcomes of content-based and collaborative searches diverge as a result. Depending on the information provided to the user, the development of her knowledge and socialization proceeds differently. A plea for customized Web search is made. It is argued that the user should be given an opportunity for selecting a combination of content-based and collaborative search that matches her interests and the context of a search query.

Suggested Citation

  • Anton Oleinik, 2022. "Relevance in Web search: between content, authority and popularity," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(1), pages 173-194, February.
    • Handle: RePEc:spr:qualqt:v:56:y:2022:i:1:d:10.1007_s11135-021-01125-7
    DOI: 10.1007/s11135-021-01125-7
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    References listed on IDEAS

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    Cited by:

    1. Sepideh Fahimifar & Khadijeh Mousavi & Fatemeh Mozaffari & Marcel Ausloos, 2023. "Identification of the most important external features of highly cited scholarly papers through 3 (i.e., Ridge, Lasso, and Boruta) feature selection data mining methods," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3685-3712, August.
    2. Anton Oleinik, 2024. "A Bayesian index of association: comparison with other measures and performance," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 277-305, February.

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