Science models for search: a study on combining scholarly information retrieval and scientometrics

Peter Mutschke () and Philipp Mayr ()
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Peter Mutschke: GESIS–Leibniz-Institute for the Social Sciences
Philipp Mayr: GESIS–Leibniz-Institute for the Social Sciences

Scientometrics, 2015, vol. 102, issue 3, No 32, 2323-2345

Abstract: Abstract Models of science address statistical properties and mechanisms of science. From the perspective of scholarly information retrieval (IR) science models may provide some potential to improve retrieval quality when operationalized as specific search strategies or used for rankings. From the science modeling perspective, on the other hand, scholarly IR can play the role of a validation model of science models. The paper studies the applicability and usefulness of two particular science models for re-ranking search results (Bradfordizing and author centrality). The paper provides a preliminary evaluation study that demonstrates the benefits of using science model driven ranking techniques, but also how different the quality of search results can be if different conceptualizations of science are used for ranking.

Keywords: Information retrieval; Scientometrics; Bradfordizing; Network analysis; Betweenness; Science models (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11192-014-1485-2

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