citation indicators of scientific journals

[Loet Leydesdorff]

** apologies for cross-postings

 

Local Citation Impact Environments of 9,162 Scientific Journals in 2009
<http://www.leydesdorff.net/jcr09/index.htm> 


One can click on any of the journal names below and obtain the Pajek file
corresponding to the citation impact environment ("cited") or the citation
activity environment ("citing") of the respective journal. See for further
explanation:  <http://www.leydesdorff.net/jcr04/index.htm> "Visualization of
the Citation Impact Environment of Scientific Journals: An online mapping
exercise," Journal of the Amererican Society for Information Science and
Technology 58(1), 25-38, 2007.
<http://www.leydesdorff.net/jcr04/jcr2pajek.pdf> <pdf version> Please,
provide this reference if you use the information.

 


2009

SCI <http://www.leydesdorff.net/jcr09/cited>  and Social SCI combined, cited

SCI <http://www.leydesdorff.net/jcr09/citing>  and Social SCI combined,
citing

9162 journals


The (local) matrices are since 2006 based on taking the one-percent
threshold of "total citations" after correction for within-journal
citations. This main-diagonal value is sometimes so large that it
overshadows the environment and therefore it is no longer included in
setting the threshold for the delineation of the set.

(with Lutz Bornmann), How fractional counting of citations affects the
Impact Factor: <http://www.leydesdorff.net/weighted_if/weighted_if.pdf> 

Normalization in terms of differences in citation potentials among fields of
science <http://www.leydesdorff.net/weighted_if/weighted_if.pdf> 

Journal of the American Society for Information Science and Technology
(JASIST; in press)

 

The ISI-Impact Factors suffer from a number of drawbacks, among them the
statistics-why should one use the mean and not the median?-and the
incomparability among fields of science because of systematic differences in
citation behavior among fields. Can these drawbacks be counteracted by
counting citation weights fractionally instead of using whole numbers in the
numerators? (i) Fractional citation counts are normalized in terms of the
citing sources and thus would take into account differences in citation
behavior among fields of science. (ii) Differences in the resulting
distributions can be tested statistically for their significance at
different levels of aggregation. (iii) Fractional counting can be
generalized to any document set including journals or groups of journals,
and thus the significance of differences among both small and large sets can
be tested. A list of fractionally counted Impact Factors for 2008 is
available online at http://www.leydesdorff.net/weighted_if/weighted_if.xls.
The in-between group variance among the thirteen fields of science
identified in the U.S. Science and Engineering Indicators is not
statistically significant after this normalization. Although citation
behavior differs largely between disciplines, the reflection of these
differences in fractionally counted citation distributions could not be used
as a reliable instrument for the classification. 

(with Ismael Rafols), Indicators of the Interdisciplinarity of Journals:
<http://www.leydesdorff.net/interdisc/interdisc.pdf> 

Diversity, Centrality, and Citations
<http://www.leydesdorff.net/interdisc/interdisc.pdf> 

Journal of Informetrics (2011, forthcoming)

 

A citation-based indicator for interdisciplinarity has been missing hitherto
among the set of available journal indicators. In this study, we investigate
network indicators (betweenness centrality), journal indicators (Shannon
entropy, the Gini coefficient), and more recently proposed Rao-Stirling
measures for "interdisciplinarity." The latter index combines the statistics
of both citation distributions of journals (vector-based) and distances in
citation networks among journals (matrix-based). The effects of various
normalizations are specified and measured using the matrix of 8,207 journals
contained in the Journal Citation Reports of the (Social) Science Citation
Index 2008. Betweenness centrality in symmetrical (1-mode) cosine-normalized
networks provides an indicator outperforming betweenness in the asymmetrical
(2-mode) citation network. Among the vector-based indicators, Shannon
entropy performs better than the Gini coefficient, but is sensitive to size.
Science and Nature, for example, are indicated at the top of the list. The
new diversity measure provides reasonable results when (1 - cosine) is
assumed as a measure for the distance, but results using Euclidean distances
were difficult to interpret.

 

  _____  

Loet Leydesdorff 
Amsterdam School of Communications Research (ASCoR)
Kloveniersburgwal 48, 1012 CX Amsterdam.
Tel. +31-20-525 6598; fax: +31-842239111

 <mailto:loet at leydesdorff.net> loet at leydesdorff.net ;
<http://www.leydesdorff.net/> http://www.leydesdorff.net/ 

Visiting Professor 2007-2010,  <http://www.istic.ac.cn/Eng/brief_en.html>
ISTIC, Beijing; Honorary Fellow 2007-2010,  <http://www.sussex.ac.uk/spru/>
SPRU, University of Sussex 
Now available:
<http://www.universal-publishers.com/book.php?method=ISBN&book=1581129378>
The Knowledge-Based Economy: Modeled, Measured, Simulated, 385 pp.; US$
18.95;
 <http://www.universal-publishers.com/book.php?method=ISBN&book=1581126956>
The Self-Organization of the Knowledge-Based Society ;
<http://www.universal-publishers.com/book.php?method=ISBN&book=1581126816>
The Challenge of Scientometrics

 

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