||It has been suggested that this article be merged with Citation analysis to Citation impact analysis. (Discuss) Proposed since December 2013.|
||It has been suggested that Impact factor#Other measures of impact be merged into this article. (Discuss) Proposed since December 2013.|
Citation impact can be measured in various ways.
An obvious measure is citation count, which quantifies both the usage and impact of the cited work. This is called citation analysis or bibliometrics. Among the measures that have emerged from citation analysis are the citation counts for:
- an individual article (how often it was cited);
- an author (total citations, or average citation count per article);
- a journal (average citation count for the articles in the journal).
Many measures have been proposed, beyond simple citation counts, to better quantify an individual scholar's citation impact. The best-known measures include the h-index and the g-index. Each measure has advantages and disadvantages, spanning from bias to discipline-dependence and limitations of the citation data source.
An important recent development in research on citation impact is the discovery of universality, or citation impact patterns that hold across different disciplines in the sciences, social sciences, and humanities. For example it has been shown that the number of citations received by a publication, once properly rescaled by its average across articles published in the same discipline and in the same year, follows a universal log-normal distribution that is the same in every discipline. This finding has suggested a universal citation impact measure that extends the h-index by properly rescaling citation counts and resorting publications, however the computation of such a universal measure requires the collection of extensive citation data and statistics for every discipline and year. Social crowdsourcing tools such as Scholarometer have been proposed to address this need.
While citation counts are often correlated with other measures of scholarly and scientific performance, causal statements linking a citation advantage with open access status have been contradicted by some experimental and observational studies.
Research suggests the impact of an article can be, partly, explained by superficial factors and not only by the scientific merits of an article. For instance in Medicine among other factors the number of authors, the number of references, the article length, and the presence of a colon in the title influence the impact. Whilst in Sociology the number of references, the article length, and title length are among the factors.
Automated citation indexing has changed the nature of citation analysis research, allowing millions of citations to be analyzed for large scale patterns and knowledge discovery. The first example of automated citation indexing was CiteSeer, later to be followed by Google Scholar. More recently, advanced models for a dynamic analysis of citation aging have been proposed. The latter model is even used as a predictive tool for determining the citations that might be obtained at any time of the lifetime of a corpus of publications.
- Garfield, E. (1955) Citation Indexes for Science: A New Dimension in Documentation through Association of Ideas. Science, Vol:122, No:3159, p. 108-111
- Garfield, E. (1973) Citation Frequency as a Measure of Research Activity and Performance in Essays of an Information Scientist, 1: 406-408, 1962-73, Current Contents, 5
- Garfield, E. (1988) Can Researchers Bank on Citation Analysis? Current Comments, No. 44, October 31, 1988
- Garfield, E. (1998) The use of journal impact factors and citation analysis in the evaluation of science. 41st Annual Meeting of the Council of Biology Editors, Salt Lake City, UT, May 4, 1998
- Moed, H. F. (2005a) Citation Analysis in Research Evaluation. NY Springer
- Hirsch, J. E. (15 November 2005), An index to quantify an individual's scientific research output, PNAS 102 (46): 16569–16572, arXiv:physics/0508025, Bibcode:2005PNAS..10216569H, doi:10.1073/pnas.0507655102, PMC 1283832, PMID 16275915
- Egghe, L. (2006), Theory and practise of the g-index, Scientometrics 69 (1): 131–152, doi:10.1007/s11192-006-0144-7
- Francisco M. Couto, Catia Pesquita, Tiago Grego, and Paulo Veríssimo (2009), Handling self-citations using Google Scholar, Cybermetrics 13 (1).
- Bollen, J.; Van de Sompel, H., Smith, J. and Luce, R. (2005), Toward alternative metrics of journal impact: A comparison of download and citation data, Information Processing and Management 41 (6): 1419–1440, arXiv:cs.DL/0503007, doi:10.1016/j.ipm.2005.03.024
- Brody, T., Harnad, S. and Carr, L. (2005) Earlier Web Usage Statistics as Predictors of Later Citation Impact Journal of the American Association for Information Science and Technology (JASIST)
- Kurtz, M. J.; Eichhorn, G.; Accomazzi, A.; Grant, C. S.; Demleitner, M.; Murray, S. S. (2004), The Effect of Use and Access on Citations, Information Processing and Management 41 (6): 1395–1402, doi:10.1016/j.ipm.2005.03.010.
- Moed, H. F. (2005b), Statistical Relationships Between Downloads and Citations at the Level of Individual Documents Within a Single Journal, Journal of the American Society for Information Science and Technology 56 (10): 1088–1097, doi:10.1002/asi.20200.
- Radicchi, F.; Fortunato, S. and Castellano, C (11 November 2008), Universality of citation distributions: Toward an objective measure of scientific impact, PNAS 105 (45): 17268–17272, arXiv:0806.0974, Bibcode:2008PNAS..10517268R, doi:10.1073/pnas.0806977105, PMC 2582263, PMID 18978030
- Hoang, D.; Kaur, J. and Menczer, F. (2010), Crowdsourcing Scholarly Data, Proceedings of the WebSci10: Extending the Frontiers of Society On-Line, April 26-27th, 2010, Raleigh, NC: US
- Bibliography of Findings on the Open Access Impact Advantage
- Brody, T.; Harnad, S. (2004), Comparing the Impact of Open Access (OA) vs. Non-OA Articles in the Same Journals, D-Lib Magazine 10: 6.
- Eysenbach G. (2006a) Citation Advantage of Open Access Articles. PLoS Biol. 2006;4(5) p. e157. Shows the Open Access citation advantage over non-Open Access papers, as well as a gold-OA over green-OA citation advantage. in the Proceedings of the National Academy of Sciences (PNAS)
- Eysenbach G (2006b) The Open Access Advantage. J Med Internet Res 2006;8(2):e8 Some follow-up data to the Eysenbach PLoS Biol study
- Hajjem, C., Harnad, S. and Gingras, Y. (2005) Ten-Year Cross-Disciplinary Comparison of the Growth of Open Access and How It Increases Research Citation Impact IEEE Data Engineering Bulletin 28(4) pp. 39-47. The study analyzed 1,307,038 articles published across 12 years (1992-2003) in 10 disciplines (Biology, Psychology, Sociology, Health, Political Science, Economics, Education, Law, Business, Management). Comparing OA and NOA articles in the same journal/year, OA articles have consistently more citations (25%-250% varying with discipline and year)
- Lawrence, S, (2001) Online or Invisible? Nature 411 (2001) (6837): 521. Landmark paper: First demonstration of the Open Access citation advantage for self-archived papers
- MacCallum CJ & Parthasarathy H (2006) Open access increases citation rate. PLoS Biol 4(5): e176. Editorial about the Eysenbach study
- Gargouri, Y., Hajjem, C., Lariviere, V., Gingras, Y., Brody, T., Carr, L. and Harnad, S. (2010) Self-Selected or Mandated, Open Access Increases Citation Impact for Higher Quality Research. PLOS ONE 5 (10) e13636
- Davis, P. M., Lewenstein, B. V., Simon, D. H., Booth, J. G., & Connolly, M. J. L. (2008). Open access publishing, article downloads and citations: randomised trial. BMJ, 337, a568-
- Open access, readership, citations: a randomized controlled trial of scientific journal publishing FASEB J. (2011) v25 n7:2129-2134
- van Wesel, M.; Wyatt, S.; ten Haaf, J. (2014). "What a difference a colon makes: how superficial factors influence subsequent citation". Scientometrics 98 (3): 1601–1615. doi:10.1007/s11192-013-1154-x.
- Giles, C. L.; Bollacker, K.; Lawrence, S. (1998). "CiteSeer: An Automatic Citation Indexing System". DL'98 Digital Libraries, 3rd ACM Conference on Digital Libraries: 89–98. doi:10.1145/276675.276685.
- Yu, G.; Li, Y.-J. (2010). "Identification of referencing and citation processes of scientific journals based on the citation distribution model". Scientometrics 82 (2): 249–261. doi:10.1007/s11192-009-0085-z.
- Bouabid, H. (2011). "Revisiting citation aging: A model for citation distribution and life-cycle prediction". Scientometrics 88 (1): 199–211. doi:10.1007/s11192-011-0370-5.
- Chanson, Hubert (2007). "Research Quality, Publications and Impact in Civil Engineering into the 21st Century. Publish or Perish, Commercial versus Open Access, Internet versus Libraries ?". Canadian Journal of Civil Engineering 34 (8): 946–951. doi:10.1169/L07-027.
- Panaretos, J.; Malesios, C. (2009). "Assessing Scientific Research Performance and Impact with Single Indices". Scientometrics 81 (3): 635–670. doi:10.1007/s11192-008-2174-9.