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 accessAbstract
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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Citations
Cites
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
Modularity and community structure in networks
Newman, M. E. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601602103 · Cited by 12,256
Wang, Q., & Waltman, L. (2016) · Journal of Informetrics · doi:10.1016/j.joi.2016.02.003 · Cited by 417
Estimates of the Continuously Publishing Core in the Scientific Workforce
Ioannidis, J. P. A., Boyack, K. W., & Klavans, R. (2014) · PLoS ONE · doi:10.1371/journal.pone.0101698 · Cited by 160
Self-citationGarcía‐Pérez, M. A. (2010) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21372 · Cited by 101
Cited by
bibliometrix: An R-tool for comprehensive science mapping analysis
Aria, M., & Cuccurullo, C. (2017) · Journal of Informetrics · doi:10.1016/j.joi.2017.08.007 · Cited by 16,064
From Louvain to Leiden: guaranteeing well-connected communities
Traag, V. A., Waltman, L., & van Eck, N. J. (2019) · Scientific Reports · doi:10.1038/s41598-019-41695-z · Cited by 5,635
Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., Petersen, A. M., Radicchi, F., Sinatra, R., Uzzi, B., et al. (2018) · Science · doi:10.1126/science.aao0185 · Cited by 1,497
“By applying network science methods to citation networks, researchers are able to identify communities as defined by subsets of publications that frequently cite one another (6).”
Wang, Q., & Waltman, L. (2016) · Journal of Informetrics · doi:10.1016/j.joi.2016.02.003 · Cited by 417
The citation advantage of linking publications to research data
Colavizza, G., Hrynaszkiewicz, I., Staden, I., Whitaker, K., & McGillivray, B. (2020) · PLOS ONE · doi:10.1371/journal.pone.0230416 · Cited by 335
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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- 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.