Using the InCites tool of Thomson Reuters, this study compares normalized
citation impact values calculated for China, Japan, France, Germany, United
States, and the UK throughout the time period from 1981 to 2010. The citation
impact values are normalized to four subject areas: natural sciences;
engineering and technology; medical and health sciences; and agricultural
sciences. The results show an increasing trend in citation impact values for
France, the UK and especially for Germany across the last thirty years in all
subject areas.

In a recent paper entitled "Inconsistencies of Recently Proposed Citation
Impact Indicators and how to Avoid Them," Schreiber (2012, at arXiv:1202.3861)
proposed (i) a method to assess tied ranks consistently and (ii) fractional
attribution to percentile ranks in the case of relatively small samples (e.g.,
for n < 100). Schreiber's solution to the problem of how to handle tied ranks
is convincing, in my opinion (cf. Pudovkin & Garfield, 2009).

Citation distributions are so skewed that using the mean or any other central
tendency measure is ill-advised. Unlike G. Prathap's scalar measures (Energy,
Exergy, and Entropy or EEE), the Integrated Impact Indicator (I3) is based on
non-parametric statistics using the (100) percentiles of the distribution.
Observed values can be tested against expected ones; impact can be qualified at
the article level and then aggregated.

Multivariate linear regression models suggest a trade-off in allocations of
national R&D investments. Government funding, and spending in the higher
education sector, seem to encourage publications, whereas other components such
as industrial funding, and spending in the business sector, encourage
patenting. Our results help explain why the US trails the EU in publications,
because of its focus on industrial funding - some 70% of its total R&D
investment. Conversely, it also helps explain why the EU trails the US in
patenting.

Using citation analysis, sets of documents can be compared as independent
samples; for example, in terms of average citation counts using potentially
different reference sets. From this perspective, the size of samples matters
only for the identification of significant differences and estimating margins
of error. Using the percentile rank approach, differences among citation
distributions can be studied non-parametrically and in a single scheme.
Comparison among the sets clarifies that the different sizes of samples affect
the weighing of the probabilities and therefore the rankings.

Grasping the fruits of "emerging technologies" is an objective of many
government priority programs in a knowledge-based and globalizing economy. We
use the publication records (in the Science Citation Index) of two emerging
technologies to study the mechanisms of diffusion in the case of two innovation
trajectories: small interference RNA (siRNA) and nano-crystalline solar cells
(NCSC). Methods for analyzing and visualizing geographical and cognitive
diffusion are specified as indicators of different dynamics.

We present animations based on the aggregated journal-journal citations of
Leonardo during the period 1974-2008. Leonardo is mainly cited by journals
outside the arts domain for cultural reasons, for example, in neuropsychology
and physics. Articles in Leonardo itself cite a large number of journals, but
with a focus on the arts. Animations at this level of aggregation enable us to
show the history of the journal from a network perspective.

The Actor Network represents heterogeneous entities as actants (Callon et
al., 1983; 1986). Although computer programs for the visualization of social
networks increasingly allow us to represent heterogeneity in a network using
different shapes and colors for the visualization, hitherto this possibility
has scarcely been exploited (Mogoutov et al., 2008). In this contribution to
the Festschrift, I study the question of what heterogeneity can add
specifically to the visualization of a network.

The framing of issues in the mass media plays a crucial role in the public
understanding of science and technology. This article contributes to research
concerned with diachronic analysis of media frames by making an analytical
distinction between implicit and explicit media frames, and by introducing an
automated method for analysing diachronic changes of implicit frames. In
particular, we apply a semantic maps method to a case study on the newspaper
debate about artificial sweeteners, published in The New York Times (NYT)
between 1980 and 2006.

How is quality control organized in the new "Mode 2" of the production of
scientific knowledge? When institutional boundaries are increasingly blurred in
a Triple Helix of University-Industry-Government relations, criteria for
quality control in the production of scientific knowledge can be expected to
change at the interfaces. The categorization in terms of two modes of knowledge
production was introduced by Gibbons et al. (1994) in order to describe changes
in the networks of scientific communications (funding patterns, research
configurations, styles of knowledge management, etc.).

Mutual information among three or more dimensions (mu-star = - Q) has been
considered as interaction information. However, Krippendorff (2009a, 2009b) has
shown that this measure cannot be interpreted as a unique property of the
interactions and has proposed an alternative measure of interaction information
based on iterative approximation of maximum entropies. Q can then be considered
as a measure of the difference between interaction information and redundancy
generated in a model entertained by an observer.

The possibilities of using the Arts & Humanities Citation Index (A&HCI) for
journal mapping have not been sufficiently recognized because of the absence of
a Journal Citations Report (JCR) for this database.

University-industry-government relations provide a networked infrastructure
for knowledge-based innovation systems. This infrastructure organizes the
dynamic fluxes locally and the knowledge base remains emergent given these
conditions. Whereas the relations between the institutions can be measured as
variables, the interacting fluxes generate a probabilistic entropy. The mutual
information among the three institutional dimensions provides us with an
indicator of this entropy. When this indicator is negative, self-organization
can be expected.

The relationship between the "knowledge base" and the "globalization" of
communication systems is discussed from the perspective of communication
theory. I argue that inter-human communication takes place at two levels. At
the first level information is exchanged and provided with meaning and at the
second level meaning can reflexively be communicated. Human language can be
considered as the evolutionary achievement which enables us to use these two
channels of communication simultaneously.

The competitive advantages in a knowledge-based economy can no longer be
attributed to single nodes in the network. Political economies are increasingly
reshaped by knowledge-based developments that upset market equilibria and
institutional arrangements. The network coordinates the subdynamics of (i)
wealth production, (ii) organized novelty production, and (iii) private
appropriation versus public control. The interaction terms generate a complex
dynamics which cannot be expected to contain central coordination.

The use of Pearson's correlation coefficient in Author Cocitation Analysis
was compared with Salton's cosine measure in a number of recent contributions.
Unlike the Pearson correlation, the cosine is insensitive to the number of
zeros. However, one has the option of applying a logarithmic transformation in
correlation analysis. Information calculus is based on both the logarithmic
transformation and provides a non-parametric statistics. Using this methodology
one can cluster a document set in a precise way and express the differences in
terms of bits of information.

Co-words have been considered as carriers of meaning across different domains
in studies of science, technology, and society. Words and co-words, however,
obtain meaning in sentences, and sentences obtain meaning in their contexts of
use. At the science/society interface, words can be expected to have different
meanings: the codes of communication that provide meaning to words differ on
the varying sides of the interface. Furthermore, meanings and interfaces may
change over time.

Co-occurrence matrices, such as co-citation, co-word, and co-link matrices,
have been used widely in the information sciences. However, confusion and
controversy have hindered the proper statistical analysis of this data. The
underlying problem, in our opinion, involved understanding the nature of
various types of matrices. This paper discusses the difference between a
symmetrical co-citation matrix and an asymmetrical citation matrix as well as
the appropriate statistical techniques that can be applied to each of these
matrices, respectively.

From its inception, a large part of the motivation for Cognitive Science has
been the need for an interdisciplinary journal for the study of minds and
intelligent systems. One threat to the interdisciplinarity of Cognitive
Science, both the field and journal, is that it may become, or already be, too
dominated by psychologists. In 2005, psychology was a keyword for 51% of
submissions, followed distantly by linguistics (17%), artificial intelligence
(13%), neuroscience (10%), computer science (9%), and philosophy (8%).

Aggregated journal-journal citation networks based on the Journal Citation
Reports 2004 of the Science Citation Index (5968 journals) and the Social
Science Citation Index (1712 journals) are made accessible from the perspective
of any of these journals. The user is thus able to analyze the citation
environment in terms of links and graphs. Furthermore, the local impact of a
journal is defined as its share of the total citations in the specific
journal's citation environments; the vertical size of the nodes is varied
proportionally to this citation impact.

The citation impact of Environment and Planning B can be visualized using its
citation relations with journals in its environment as the links of a network.
The size of the nodes is varied in correspondence to the relative citation
impact in this environment. Additionally, one can correct for the effect of
within-journal "self"-citations. The network can be partitioned and clustered
using algorithms from social network analysis.

The journal structure in the China Scientific and Technical Papers and
Citations Database (CSTPCD) is analysed from three perspectives: the database
level, the specialty level and the institutional level (i.e., university
journals versus journals issued by the Chinese Academy of Sciences). The
results are compared with those for (Chinese) journals included in the Science
Citation Index. The frequency of journal-journal citation relations in the
CSTPCD is an order of magnitude lower than in the SCI.

Purpose: to provide a view and analysis of the immediate field of journals
which surround a number of key heterodox economics journals.
Design/methodology/approach: Using citation data from the Science and Social
Science Citation Index, the individual and collective networks of a number of
journals in this field are analyzed. Findings: The size and shape of the
citation networks of journals can differ substantially, even if in a broadly
similar category.

Discursive knowledge emerges as codification in flows of communication. The
flows of communication are constrained and enabled by networks of
communications as their historical manifestations at each moment of time. New
publications modify the existing networks by changing the distributions of
attributes and relations in document sets, while the networks are
self-referentially updated along trajectories. Codification operates
reflexively: the network structures are reconstructed from the perspective of
hindsight.