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Cited by 334

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge?

Open access
Klavans, Richard, Boyack, Kevin W.·2017·Journal of the Association for Information Science and Technology

Abstract

In 1965, Price foresaw the day when a citation‐based taxonomy of science and technology would be delineated and correspondingly used for science policy. A taxonomy needs to be comprehensive and accurate if it is to be useful for policy making, especially now that policy makers are utilizing citation‐based indicators to evaluate people, institutions and laboratories. Determining the accuracy of a taxonomy, however, remains a challenge. Previous work on the accuracy of partition solutions is sparse, and the results of those studies, although useful, have not been definitive. In this study we compare the accuracies of topic‐level taxonomies based on the clustering of documents using direct citation, bibliographic coupling, and co‐citation. Using a set of new gold standards—articles with at least 100 references—we find that direct citation is better at concentrating references than either bibliographic coupling or co‐citation. Using the assumption that higher concentrations of references denote more accurate clusters, direct citation thus provides a more accurate representation of the taxonomy of scientific and technical knowledge than either bibliographic coupling or co‐citation. We also find that discipline‐level taxonomies based on journal schema are highly inaccurate compared to topic‐level taxonomies, and recommend against their use.

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Metadata

Authors
Klavans, R., & Boyack, K. W.
Venue
Journal of the Association for Information Science and Technology
Publisher
Wiley
Published
2016-10-13
Volume
68
Issue
4
Pages
984-998
ISSN
  • 2330-1635 (ISSN-L)
  • 2330-1643
OpenAlex
W3103443220
Cited by
334
References
5
FWCI
26.89
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge? https://app.cochat.ai/papers/10.1002/asi.23734
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Klavans, R., & Boyack, K. W. (2017). Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge? Journal of the Association for Information Science and Technology. https://doi.org/10.1002/asi.23734

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.