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Does High Impact Factor Successfully Predict Future Citations? An Analysis Using Peirce’s Measure

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dc.contributor.author Gangan Prathap
dc.contributor.author Mini, S
dc.contributor.author Nishy, P
dc.date.accessioned 2017-05-25T06:27:53Z
dc.date.available 2017-05-25T06:27:53Z
dc.date.issued 2016-09
dc.identifier.citation Scientometrics 108:1043–1047 en_US
dc.identifier.uri http://hdl.handle.net/123456789/2808
dc.description.abstract Journals are routinely evaluated by journal impact factors. However, more controversially, these same impact factors are often used to evaluate authors and groups as well. A more meaningful approach will be to use actual citation rates. Since in each journal there is a very highly skewed distribution of articles according to citation rates, there is little correlation between journal impact factor and actual citation rate of articles from individual scientists or research groups. Simply stated, journal impact factor does not successfully predict high citations in future. In this paper, we propose the use of Peirce’s measure of predictive success (Peirce in Science 4(93):453–454, 1884) to see if the use of journal impact factors to predict high citation rates is acceptable or not. It is seen that this measure is independent of Pearson’s correlation (Seglen 1997) and gives a more quantitative refinement of the Type I and Type II classification of Smith (Financ Manag 133–149, 2004). The measures are used to examine the portfolios of some active scientists. It is clear that the journal impact factor is not effective in predicting future citations of successful authors. en_US
dc.language.iso en en_US
dc.publisher spinger en_US
dc.subject Performance analysis en_US
dc.subject Bibliometrics en_US
dc.subject Impact factor en_US
dc.subject Citations en_US
dc.subject Peirce’s measure en_US
dc.title Does High Impact Factor Successfully Predict Future Citations? An Analysis Using Peirce’s Measure en_US
dc.title.alternative Scientometrics (2016) 108:1043–1047 en_US
dc.type Article en_US


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