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Alternatives to the Journal Impact Factor:
I3 and the Top-10% (or Top-25%?) of the Most-Highly Cited Papers
< http://arxiv.org/ftp/arxiv/papers/1201/1201.4638.pdf >
Journal Impact Factors can be considered historically as the first attempt
to normalize citation distributions by using averages over two years.
However, it has been recognized that citation distributions vary among
fields of science and that one needs to normalize for this. Furthermore, the
mean--or any central-tendency statistics--is not a good representation of
the citation distribution because these distributions are skewed. Important
steps have been taken to solve these two problems during the last few years.
First, one can normalize at the article level using the citing audience as
the reference set. Second, one can use non-parametric statistics for testing
the significance of differences among ratings. A proportion of most-highly
cited papers (the top-10% or top-quartile) on the basis of fractional
counting of the citations may provide an alternative to the current IF. This
indicator is intuitively simple, allows for statistical testing, and accords
with the state of the art.
Professor, University of Amsterdam
Amsterdam School of Communications Research (ASCoR)
Kloveniersburgwal 48, 1012 CX Amsterdam.
Tel. +31-20-525 6598; fax: +31-842239111
[log in to unmask] ; http://www.leydesdorff.net/
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