25,683 research outputs found
Constructing bibliometric networks: A comparison between full and fractional counting
The analysis of bibliometric networks, such as co-authorship, bibliographic
coupling, and co-citation networks, has received a considerable amount of
attention. Much less attention has been paid to the construction of these
networks. We point out that different approaches can be taken to construct a
bibliometric network. Normally the full counting approach is used, but we
propose an alternative fractional counting approach. The basic idea of the
fractional counting approach is that each action, such as co-authoring or
citing a publication, should have equal weight, regardless of for instance the
number of authors, citations, or references of a publication. We present two
empirical analyses in which the full and fractional counting approaches yield
very different results. These analyses deal with co-authorship networks of
universities and bibliographic coupling networks of journals. Based on
theoretical considerations and on the empirical analyses, we conclude that for
many purposes the fractional counting approach is preferable over the full
counting one
Correlated fractional counting processes on a finite time interval
We present some correlated fractional counting processes on a finite time
interval. This will be done by considering a slight generalization of the
processes in Borges et al. (2012). The main case concerns a class of space-time
fractional Poisson processes and, when the correlation parameter is equal to
zero, the univariate distributions coincide with the ones of the space-time
fractional Poisson process in Orsingher and Polito (2012). On the other hand,
when we consider the time fractional Poisson process, the multivariate finite
dimensional distributions are different from the ones presented for the renewal
process in Politi et al. (2011). Another case concerns a class of fractional
negative binomial processes
A review of the characteristics of 108 author-level bibliometric indicators
An increasing demand for bibliometric assessment of individuals has led to a
growth of new bibliometric indicators as well as new variants or combinations
of established ones. The aim of this review is to contribute with objective
facts about the usefulness of bibliometric indicators of the effects of
publication activity at the individual level. This paper reviews 108 indicators
that can potentially be used to measure performance on the individual author
level, and examines the complexity of their calculations in relation to what
they are supposed to reflect and ease of end-user application.Comment: to be published in Scientometrics, 201
A review of the literature on citation impact indicators
Citation impact indicators nowadays play an important role in research
evaluation, and consequently these indicators have received a lot of attention
in the bibliometric and scientometric literature. This paper provides an
in-depth review of the literature on citation impact indicators. First, an
overview is given of the literature on bibliographic databases that can be used
to calculate citation impact indicators (Web of Science, Scopus, and Google
Scholar). Next, selected topics in the literature on citation impact indicators
are reviewed in detail. The first topic is the selection of publications and
citations to be included in the calculation of citation impact indicators. The
second topic is the normalization of citation impact indicators, in particular
normalization for field differences. Counting methods for dealing with
co-authored publications are the third topic, and citation impact indicators
for journals are the last topic. The paper concludes by offering some
recommendations for future research
Scopus's Source Normalized Impact per Paper (SNIP) versus a Journal Impact Factor based on Fractional Counting of Citations
Impact factors (and similar measures such as the Scimago Journal Rankings)
suffer from two problems: (i) citation behavior varies among fields of science
and therefore leads to systematic differences, and (ii) there are no statistics
to inform us whether differences are significant. The recently introduced SNIP
indicator of Scopus tries to remedy the first of these two problems, but a
number of normalization decisions are involved which makes it impossible to
test for significance. Using fractional counting of citations-based on the
assumption that impact is proportionate to the number of references in the
citing documents-citations can be contextualized at the paper level and
aggregated impacts of sets can be tested for their significance. It can be
shown that the weighted impact of Annals of Mathematics (0.247) is not so much
lower than that of Molecular Cell (0.386) despite a five-fold difference
between their impact factors (2.793 and 13.156, respectively)
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