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Citation Patterns of Engineering, Statistics, and Computer Science Researchers: An Internal and External Citation Analysis across Multiple Engineering Subfields
Author(s) -
Madeline Kelly
Publication year - 2015
Publication title -
college and research libraries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.886
H-Index - 52
eISSN - 2150-6701
pISSN - 0010-0870
DOI - 10.5860/crl.76.7.859
Subject(s) - citation , citation analysis , computer science , data science , science and engineering , information retrieval , library science , engineering ethics , engineering
This study takes a multidimensional approach to citation analysis, examining citations in multiple subfields of engineering, from both scholarly journals and doctoral dissertations. The three major goals of the study are to determine whether there are differences between citations drawn from dissertations and those drawn from journal articles; to test a methodology incorporating both internal and external citation sources; and to explore the citation habits of researchers in science, technology, engineering, and mathematics (STEM) subfields. The results reveal variations in how STEM subfields conduct research in career and academic settings and are more nuanced than internal or external citation data alone can provide. The results have practical collection development implications.

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