Journal ArticleDOI
Relevance in Web search: between content, authority and popularity
Anton Oleinik,Anton Oleinik +1 more
TLDR
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.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.read more
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Book
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