Citation Patterns of Engineering, Statistics, and Computer Science Researchers: An Internal and External Citation Analysis across Multiple Engineering Subfields

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dc.contributor.authorKelly, Madeline
dc.date.accessioned2015-11-16T15:17:36Z
dc.date.available2015-11-16T15:17:36Z
dc.date.issued2015-11
dc.description.abstractThis 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.
dc.identifier.citationKelly, M. (2015). Citation Patterns of Engineering, Statistics, and Computer Science Researchers: An Internal and External Citation Analysis across Multiple Engineering Subfields. College & Research Libraries, 76(7), 859-882. http://doi.org/10.5860/crl.76.7.859
dc.identifier.doihttp://dx.doi.org/10.5860/crl.76.7.859
dc.identifier.urihttps://hdl.handle.net/1920/10016
dc.language.isoen_US
dc.publisherAmerican Library Association
dc.rightsAttribution-NonCommercial 3.0 United States
dc.rights.urihttps://creativecommons.org/licenses/by-nc/3.0/us/
dc.subjectCitation analysis
dc.subject.lcshEngineering
dc.subject.lcshCollection development
dc.titleCitation Patterns of Engineering, Statistics, and Computer Science Researchers: An Internal and External Citation Analysis across Multiple Engineering Subfields
dc.typeArticle

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