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Peter Mutschke GESIS-Leibniz Institute for the Social Sciences, Lennéstr. 30, 53111 Bonn, Germany

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Philipp Mayr GESIS-Leibniz Institute for the Social Sciences, Lennéstr. 30, 53111 Bonn, Germany

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Philipp Schaer GESIS-Leibniz Institute for the Social Sciences, Lennéstr. 30, 53111 Bonn, Germany

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York Sure GESIS-Leibniz Institute for the Social Sciences, Lennéstr. 30, 53111 Bonn, Germany

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Abstract

The paper introduces scholarly Information Retrieval (IR) as a further dimension that should be considered in the science modeling debate. The IR use case is seen as a validation model of the adequacy of science models in representing and predicting structure and dynamics in science. Particular conceptualizations of scholarly activity and structures in science are used as value-added search services to improve retrieval quality: a co-word model depicting the cognitive structure of a field (used for query expansion), the Bradford law of information concentration, and a model of co-authorship networks (both used for re-ranking search results). An evaluation of the retrieval quality when science model driven services are used turned out that the models proposed actually provide beneficial effects to retrieval quality. From an IR perspective, the models studied are therefore verified as expressive conceptualizations of central phenomena in science. Thus, it could be shown that the IR perspective can significantly contribute to a better understanding of scholarly structures and activities.

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Scientometrics
Language English
Size B5
Year of
Foundation
1978
Volumes
per Year
1
Issues
per Year
12
Founder Akadémiai Kiadó
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H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
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Springer Nature Switzerland AG
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Chief Executive Officer, Akadémiai Kiadó
ISSN 0138-9130 (Print)
ISSN 1588-2861 (Online)

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