161 research outputs found
The Leiden Ranking 2011/2012: Data collection, indicators, and interpretation
The Leiden Ranking 2011/2012 is a ranking of universities based on
bibliometric indicators of publication output, citation impact, and scientific
collaboration. The ranking includes 500 major universities from 41 different
countries. This paper provides an extensive discussion of the Leiden Ranking
2011/2012. The ranking is compared with other global university rankings, in
particular the Academic Ranking of World Universities (commonly known as the
Shanghai Ranking) and the Times Higher Education World University Rankings.
Also, a detailed description is offered of the data collection methodology of
the Leiden Ranking 2011/2012 and of the indicators used in the ranking. Various
innovations in the Leiden Ranking 2011/2012 are presented. These innovations
include (1) an indicator based on counting a university's highly cited
publications, (2) indicators based on fractional rather than full counting of
collaborative publications, (3) the possibility of excluding non-English
language publications, and (4) the use of stability intervals. Finally, some
comments are made on the interpretation of the ranking, and a number of
limitations of the ranking are pointed out
The revised SNIP indicator of Elsevier's Scopus
The modified SNIP indicator of Elsevier, as recently explained by Waltman et
al. (2013) in this journal, solves some of the problems which Leydesdorff &
Opthof (2010 and 2011) indicated in relation to the original SNIP indicator
(Moed, 2010 and 2011). The use of an arithmetic average, however, remains
unfortunate in the case of scientometric distributions because these can be
extremely skewed (Seglen, 1992 and 1997). The new indicator cannot (or hardly)
be reproduced independently when used for evaluation purposes, and remains in
this sense opaque from the perspective of evaluated units and scholars.Comment: Letter to the Editor of the Journal of Informetrics (2013; in press
An Integrated Impact Indicator (I3): A New Definition of "Impact" with Policy Relevance
Allocation of research funding, as well as promotion and tenure decisions,
are increasingly made using indicators and impact factors drawn from citations
to published work. A debate among scientometricians about proper normalization
of citation counts has resolved with the creation of an Integrated Impact
Indicator (I3) that solves a number of problems found among previously used
indicators. The I3 applies non-parametric statistics using percentiles,
allowing highly-cited papers to be weighted more than less-cited ones. It
further allows unbundling of venues (i.e., journals or databases) at the
article level. Measures at the article level can be re-aggregated in terms of
units of evaluation. At the venue level, the I3 creates a properly weighted
alternative to the journal impact factor. I3 has the added advantage of
enabling and quantifying classifications such as the six percentile rank
classes used by the National Science Board's Science & Engineering Indicators.Comment: Research Evaluation (in press
How to improve the prediction based on citation impact percentiles for years shortly after the publication date?
The findings of Bornmann, Leydesdorff, and Wang (in press) revealed that the
consideration of journal impact improves the prediction of long-term citation
impact. This paper further explores the possibility of improving citation
impact measurements on the base of a short citation window by the consideration
of journal impact and other variables, such as the number of authors, the
number of cited references, and the number of pages. The dataset contains
475,391 journal papers published in 1980 and indexed in Web of Science (WoS,
Thomson Reuters), and all annual citation counts (from 1980 to 2010) for these
papers. As an indicator of citation impact, we used percentiles of citations
calculated using the approach of Hazen (1914). Our results show that citation
impact measurement can really be improved: If factors generally influencing
citation impact are considered in the statistical analysis, the explained
variance in the long-term citation impact can be much increased. However, this
increase is only visible when using the years shortly after publication but not
when using later years.Comment: Accepted for publication in the Journal of Informetrics. arXiv admin
note: text overlap with arXiv:1306.445
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