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

By Richard Klavans, Kevin W. Boyack. J. Assoc. Inf. Sci. Technol., 2015

322 citations recorded by the source corpus.

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.

Subfields: Information Systems, Molecular Biology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/adf4913bb6bb12fd533b4f608eff1ce2cbabab92

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Citations in the corpus

Social innovation research: An emerging area of innovation studies? (2016, result): “…that BC produced slightly more accurate clustering results than the commonly used method of co-citation, but noted recently that because BC is somewhat more sensitive to recent common references than co-citation (cf.van Raan, 2005), this may explain their earlier result (Klavans and Boyack, 2016).”
From Louvain to Leiden: guaranteeing well-connected communities (2018, background): “Similarly, in citation networks, such as the Web of Science network, nodes in a community are usually considered to share a common topic 26,27 .”