The Citation Cloud of a biomedical article: a free, public, web-based tool enabling citation analysis
DOI:
https://doi.org/10.5195/jmla.2022.1117Keywords:
citation analysis, bibliometrics, information retrieval, evidence based medicine, science of scienceAbstract
Background: An article’s citations are useful for finding related articles that may not be readily found by keyword searches or textual similarity. Citation analysis is also important for analyzing scientific innovation and the structure of the biomedical literature. We wanted to facilitate citation analysis for the broad community by providing a user-friendly interface for accessing and analyzing citation data for biomedical articles.
Case Presentation: We seeded the Citation Cloud dataset with over 465 million open access citations culled from six different sources: PubMed Central, Microsoft Academic Graph, ArnetMiner, Semantic Scholar, Open Citations, and the NIH iCite dataset. We implemented a free, public extension to PubMed that allows any user to visualize and analyze the entire citation cloud around any paper of interest A: the set of articles cited by A, those which cite A, those which are co-cited with A, and those which are bibliographically coupled to A.
Conclusions: Citation Cloud greatly enables the study of citations by the scientific community, including relatively advanced analyses (co-citations and bibliographic coupling) that cannot be undertaken using other available tools. The tool can be accessed by running any PubMed query on the Anne O’Tate value-added search interface and clicking on the Citations button next to any retrieved article.
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Copyright (c) 2022 Neil R. Smalheiser, Jodi Schneider, Vetle I. Torvik, Dean P. Fragnito, Eric E. Tirk
This work is licensed under a Creative Commons Attribution 4.0 International License.
