24 research outputs found
Climate Change Research in View of Bibliometrics
This bibliometric study of a large publication set dealing with research on
climate change aims at mapping the relevant literature from a bibliometric
perspective and presents a multitude of quantitative data: (1) The growth of
the overall publication output as well as (2) of some major subfields, (3) the
contributing journals and countries as well as their citation impact, and (4) a
title word analysis aiming to illustrate the time evolution and relative
importance of specific research topics. The study is based on 222,060 papers
published between 1980 and 2014. The total number of papers shows a strong
increase with a doubling every 5-6 years. Continental biomass related research
is the major subfield, closely followed by climate modeling. Research dealing
with adaptation, mitigation, risks, and vulnerability of global warming is
comparatively small, but their share of papers increased exponentially since
2005. Research on vulnerability and on adaptation published the largest
proportion of very important papers. Research on climate change is
quantitatively dominated by the USA, followed by the UK, Germany, and Canada.
The citation-based indicators exhibit consistently that the UK has produced the
largest proportion of high impact papers compared to the other countries
(having published more than 10,000 papers). The title word analysis shows that
the term climate change comes forward with time. Furthermore, the term impact
arises and points to research dealing with the various effects of climate
change. Finally, the term model and related terms prominently appear
independent of time, indicating the high relevance of climate modeling.Comment: 40 pages, 6 figures, and 4 table
Generating clustered journal maps: an automated system for hierarchical classification
Journal maps and classifications for 11,359 journals listed in the combined
Journal Citation Reports 2015 of the Science and Social Sciences Citation Indexes are
provided at https://leydesdorff.github.io/journals/ and http://www.leydesdorff.net/jcr15. A
routine using VOSviewer for integrating the journal mapping and their hierarchical clusterings
is also made available. In this short communication, we provide background on the
journal mapping/clustering and an explanation about and instructions for the routine. We
compare journal maps for 2015 with those for 2014 and show the delineations among fields
and subfields to be sensitive to fluctuations. Labels for fields and sub-fields are not provided
by the routine, but an analyst can add them for pragmatic or intellectual reasons. The
routine provides a means of testing one’s assumptions against a baseline without claiming
authority; clusters of related journals can be visualized to understand communities. The
routine is generic and can be used for any 1-mode network
Methods for the generation of normalized citation impact scores in bibliometrics: Which method best reflects the judgements of experts?
Evaluative bibliometrics compares the citation impact of researchers,
research groups and institutions with each other across time scales and
disciplines. Both factors - discipline and period - have an influence on the
citation count which is independent of the quality of the publication.
Normalizing the citation impact of papers for these two factors started in the
mid-1980s. Since then, a range of different methods have been presented for
producing normalized citation impact scores. The current study uses a data set
of over 50,000 records to test which of the methods so far presented correlate
better with the assessment of papers by peers. The peer assessments come from
F1000Prime - a post-publication peer review system of the biomedical
literature. Of the normalized indicators, the current study involves not only
cited-side indicators, such as the mean normalized citation score, but also
citing-side indicators. As the results show, the correlations of the indicators
with the peer assessments all turn out to be very similar. Since F1000 focuses
on biomedicine, it is important that the results of this study are validated by
other studies based on datasets from other disciplines or (ideally) based on
multi-disciplinary datasets.Comment: Accepted for publication in the Journal of Informetric