Compara mètodes

	Reference Accuracy Study	Citation Analysis for Collection Development	Citation Context Analysis
Camp	Library Information Science	Library Information Science	Library Information Science
Família	Process / pipeline	Process / pipeline	Process / pipeline
Any d'origen	2017	2005	1975
Autor original	Biomedical and library science literature on citation accuracy; Scott A. Mogull (synthesis)	Library collection-development literature; Jennifer E. Knievel & Charlene Kellsey (comparative humanities study)	Michael J. Moravcsik & Poovanalingam Murugesan
Tipus	Verification pipeline estimating bibliographic and quotation error rates in reference lists	Bibliometric pipeline applying local citation patterns to collection-building decisions	Content-analytic pipeline for classifying the function and sentiment of in-text citations
Font seminal	Mogull, S. A. (2017). Accuracy of cited "facts" in medical research articles: A review of study methodology and recalculation of quotation error rate. PLOS ONE, 12(9), e0184727.	Knievel, J. E., & Kellsey, C. (2005). Citation Analysis for Collection Development: A Comparative Study of Eight Humanities Fields. The Library Quarterly, 75(2), 142-168.	Moravcsik, M. J., & Murugesan, P. (1975). Some Results on the Function and Quality of Citations. Social Studies of Science, 5(1), 86-92.
Àlies	Citation Error Analysis, Quotation Error Study, Reference Verification Study, Citation Accuracy Audit	Local Citation Analysis, Citation-Based Collection Evaluation, Reference Citation Study, Citation Analysis for Acquisitions	Citation Function Analysis, Citation Content Analysis, Citation Sentiment Analysis, Citation Classification
Relacionats	2	3	2
Resum	A reference accuracy study verifies the references in published work against their sources to estimate how often citations are wrong, distinguishing bibliographic errors (mistakes in author, title, year, volume, or pages) from quotation errors (cases where the cited source does not actually support the claim attributed to it). The method draws a sample of references, checks each one against the original document, and reports error rates as proportions with confidence intervals, often classifying errors by severity. Such studies have repeatedly found troubling rates: reviews of medical research, synthesized by Mogull (2017), put the quotation error rate near 14.5 percent, and Smith and Cumberledge (2020) found substantial quotation errors even in general science journals. For libraries and editors, these studies justify citation-checking services and reference-verification workflows.	Citation analysis for collection development studies what a library's own community actually cites, in their theses, dissertations, and publications, and uses those patterns to guide what the library should buy, keep, and cancel. Rather than mapping the global structure of a field, it asks a local, practical question: which formats, languages, ages, and specific titles do our researchers rely on? By tabulating the references in locally produced scholarship, the method reveals, for example, whether a discipline depends on monographs or journals, how quickly its literature ages, and which journals or books appear most often, evidence that can be matched against holdings to find gaps and guide budgets. Knievel and Kellsey's comparative study of eight humanities fields showed how sharply these citation patterns vary by discipline, underscoring why collection decisions should rest on field-specific local evidence.	Citation context analysis looks past the bare count of citations to ask why and how a work is cited, by reading the text surrounding each in-text reference and classifying its function, sentiment, and content. Where ordinary citation counting treats every reference as an equal vote, this method recognizes that citations differ: some are central to a paper's argument and others merely perfunctory, some confirm a cited finding and others dispute it, some use a method and others only mention a concept. Moravcsik and Murugesan's 1975 study of theoretical physics introduced the now-classic functional distinctions (conceptual versus operational, organic versus perfunctory, evolutionary versus juxtapositional, confirmative versus negational) and found that a large share of citations were perfunctory, casting doubt on citation counts as pure quality measures. Tahamtan and Bornmann's review situates this work within the broader question of what citation counts actually measure.