Using Data Mining for Citation Analysis

Autor/in	White, Philip B.
Titel	Using Data Mining for Citation Analysis
Quelle	In: College & Research Libraries, 80 (2019) 1, S.76-93 (18 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0010-0870
Schlagwörter	Data Analysis; Citation Analysis; Citations (References); Faculty Publishing; Geology; Universities; College Faculty; Databases; Library Materials; Periodicals; Earth Science; Academic Libraries; Colorado (Boulder) + Suchen Sie Ihr Suchwort? Auswertung; Citation; Citations; Zitatenanalyse; Zitat; Historische Geologie; University; Universität; Fakultät; Datenbank; Periodical; Journal; Zeitschrift; Fachzeitschrift; Periodikum; Earth sciences; Geowissenschaften; College; Colleges; Universities; Libary; Libraries; Hochschule; Fachhochschule; Bibliothek; Hochschulbibliothek
Abstract	This paper presents a new model for citation analysis, applying new methodological approaches in citation studies. These methods are demonstrated by an analysis of cited references from publications by the Geological Sciences faculty at the University of Colorado Boulder. The author made use of simple Python scripting, the Web of Science API, and OpenRefine to examine the most frequently cited journals and compare them to library holdings data to discover materials absent from the local collection. Of the more than 20,000 citations analyzed, 80 percent cited approximately 10 percent of all titles (412 journals). A notable finding was the heavy reliance of faculty members upon works between zero and two years of age. The streamlined model presented here removes the constraints of time and effort encountered by academic librarians interested in conducting citation analyses. (As Provided).
Anmerkungen	Association of College and Research Libraries. 50 East Huron Street, Chicago, IL 60611. e-mail: acrl@ala.org; Web site: http://crl.acrl.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01