Comparison of topic extraction approaches and their results

Theresa Velden (), Kevin W. Boyack (), Jochen Gläser (), Rob Koopman (), Andrea Scharnhorst () and Shenghui Wang ()
Additional contact information
Theresa Velden: University of Michigan School of Information
Kevin W. Boyack: SciTech Strategies, Inc.
Jochen Gläser: Technical University Berlin
Rob Koopman: OCLC Research
Andrea Scharnhorst: DANS-KNAW
Shenghui Wang: OCLC Research

Scientometrics, 2017, vol. 111, issue 2, No 30, 1169-1221

Abstract: Abstract This is the last paper in the Synthesis section of this special issue on ‘Same Data, Different Results’. We first provide a framework of how to describe and distinguish approaches to topic extraction from bibliographic data of scientific publications. We then compare solutions delivered by the different topic extraction approaches in this special issue, and explore where they agree and differ. This is achieved without reference to a ground truth, since we have to assume the existence of multiple, equally important, valid perspectives and want to avoid bias through the adoption of an ad-hoc yardstick. Instead, we apply different ways to quantitatively and visually compare solutions to explore their commonalities and differences and develop hypotheses about the origin of these differences. We conclude with a discussion of future work needed to develop methods for comparison and validation of topic extraction results, and express our concern about the lack of access to non-proprietary benchmark data sets to support method development in the field of scientometrics.

Keywords: Topic extraction; Comparative methods; Astrophysics; Data modeling; Clustering; Topic labeling; Science mapping (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (30)

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DOI: 10.1007/s11192-017-2306-1

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