CiteGraph: a citation network system for MEDLINE articles and analysis.
This paper details the development and implementation of CiteGraph, a system for constructing large-scale citation and co-authorship networks from full-text biomedical articles. CiteGraph represents articles and authors by uniquely identified nodes, and connects those nodes through citation and co-authorship relations. CiteGraph network encompasses over 1.65 million full-text articles and 6.35 million citations by 1.37 million unique authors from the Elsevier full-text articles. Our evaluation shows 98% 99% F1-score for mapping a citation to the corresponding article and identifying MEDLINE articles. We further analyzed the characteristics of CiteGraph and found that they are consistent with assumptions made using small-scale bibliometric analysis. We also developed several novel network-based methods for analyzing publication, citation and collaboration patterns. This is the first work to develop a completely automated system for the creation of a large-scale citation network in the biomedical domain, and also to introduce novel findings in researcher publication histories. CiteGraph can be a useful resource to both the biomedical community, and bibliometric research.
Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
Qing
Q
Zhang
Hong
H
Yu
D001185:Artificial Intelligence; D015706:Bibliometrics; D003628:Database Management Systems; D016239:MEDLINE / Q000706:statistics & numerical data*; D008498:Medical Record Linkage / Q000379:methods*; D009323:Natural Language Processing; D010506:Periodicals as Topic / Q000706:statistics & numerical data*; D018875:Vocabulary, Controlled