Databases provide citation counts and other metrics across a range of disciplines. No database has complete coverage of all publications. It is important to check their scope and use multiple sources to accurately represent your citation impact.
Citation analysis was traditionally based on data from the ISI Citation indexes. Now with the appearance of Scopus, and with the free citation tool Google Scholar methods and measures are need for comparing these tools. In this paper we propose a set of measures for computing the similarity between rankings induced by ordering the retrieved publications in decreasing order of the number of citations as reported by the specific tools. The applicability of these measures is demonstrated and the results show high similarities between the rankings of the ISI Web of Science and Scopus and lower similarities between Google Scholar and the other tools.
F. Arnold, und R. Jäschke. Proceedings of the Workshop Understanding LIterature references in academic full TExt at JCDL 2022, Volume 3220 von ULITE-ws '22, Seite 7--15. CEUR Workshop Proceedings, (2022)
G. Sautter, K. Böhm, und D. King. Digital Libraries: Social Media and Community Networks, Seite 161--170. Cham, Springer International Publishing, (2013)
G. Muzny, M. Fang, A. Chang, und D. Jurafsky. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, Seite 460--470. Valencia, Spain, Association for Computational Linguistics, (April 2017)
C. Scheible, R. Klinger, und S. Padó. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Seite 1736--1745. Berlin, Germany, Association for Computational Linguistics, (August 2016)
R. Yan, J. Tang, X. Liu, D. Shan, und X. Li. Proceedings of the 20th ACM international conference on Information and knowledge management, Seite 1247--1252. New York, NY, USA, ACM, (2011)