Many investigations of scientific collaboration are based on statistical analyses of large networks constructed from bibliographic
repositories. These investigations often rely on a wealth of bibliographic data, but very little or no other information about
the individuals in the network, and thus, fail to illustrate the broader social and academic landscape in which collaboration
takes place. In this article, we perform an in-depth longitudinal analysis of a relatively small network of scientific collaboration
(N = 291) constructed from the bibliographic record of a research centerin the development and application of wireless and sensor
network technologies. We perform a preliminary analysis of selected structural properties of the network, computing its range,
configuration and topology. We then support our preliminary statistical analysis with an in-depth temporal investigation of
the assortative mixing of selected node characteristics, unveiling the researchers’ propensity to collaborate preferentially
with others with a similar academic profile. Our qualitative analysis of mixing patterns offers clues as to the nature of
the scientific community being modeled in relation to its organizational, disciplinary, institutional, and international arrangements
We present VOSviewer, a freely available computer program that we have developed for constructing and viewing bibliometric
maps. Unlike most computer programs that are used for bibliometric mapping, VOSviewer pays special attention to the graphical
representation of bibliometric maps. The functionality of VOSviewer is especially useful for displaying large bibliometric
maps in an easy-to-interpret way. The paper consists of three parts. In the first part, an overview of VOSviewer’s functionality
for displaying bibliometric maps is provided. In the second part, the technical implementation of specific parts of the program
is discussed. Finally, in the third part, VOSviewer’s ability to handle large maps is demonstrated by using the program to
construct and display a co-citation map of 5,000 major scientific journals.
Bibliometric counting methods need to be validated against perceived notions of authorship credit allocation, and standardized
by rejecting methods with poor fit or questionable ethical implications. Harmonic counting meets these concerns by exhibiting
a robust fit to previously published empirical data from medicine, psychology and chemistry, and by complying with three basic
ethical criteria for the equitable sharing of authorship credit. Harmonic counting can also incorporate additional byline
information about equal contribution, or the elevated status of a corresponding last author. By contrast, several previously
proposed counting schemes from the bibliometric literature including arithmetic, geometric and fractional counting, do not
fit the empirical data as well and do not consistently meet the ethical criteria. In conclusion, harmonic counting would seem
to provide unrivalled accuracy, fairness and flexibility to the long overdue task of standardizing bibliometric allocation
of publication and citation credit.
In this study the amount of “informal” citations (i.e. those mentioning only author names or their initials instead of the
complete references) in comparison to the “formal” (full reference based) citations is analyzed using some pioneers of chemistry
and physics as examples. The data reveal that the formal citations often measure only a small fraction of the overall impact
of seminal publications. Furthermore, informal citations are mainly given instead of (and not in addition to) formal citations.
As a major consequence, the overall impact of pioneering articles and researchers cannot be entirely determined by merely
counting the full reference based citations.
Authors:Thomas Anderson, Robin Hankin, and Peter Killworth
An individual’s h-index corresponds to the number h of his/her papers that each has at least h citations. When the citation count of an article exceeds h, however, as is the case for the hundreds or even thousands of citations that accompany the most highly cited papers, no
additional credit is given (these citations falling outside the so-called “Durfee square”). We propose a new bibliometric
index, the “tapered h-index” (hT), that positively enumerates all citations, yet scoring them on an equitable basis with h.
The career progression of hT and h are compared for six eminent scientists in contrasting fields. Calculated hT for year 2006 ranged between 44.32 and 72.03, with a corresponding range in h of 26 to 44. We argue that the hT-index is superior to h, both theoretically (it scores all citations), and because it shows smooth increases from year to year as compared with the
irregular jumps seen in h. Conversely, the original h-index has the benefit of being conceptually easy to visualise. Qualitatively, the two indices show remarkable similarity
(they are closely correlated), such that either can be applied with confidence.
Authors:Iina Hellsten, Renaud Lambiotte, Andrea Scharnhorst, and Marcel Ausloos
This paper introduces a new approach to detecting scientists’ field mobility by focusing on an author’s self-citation network,
and the co-authorships and keywords in self-citing articles. Contrary to much previous literature on self-citations, we will
show that author’s self-citation patterns reveal important information on the development and emergence of new research topics
over time. More specifically, we will discuss self-citations as a means to detect scientists’ field mobility. We introduce
a network based definition of field mobility, using the Optimal Percolation Method (Lambiotte & Ausloos, 2005; 2006). The results of the study can be extended to selfcitation networks of groups of authors and, generally also
for other types of networks.
Innovation research builds on the analysis of micro level data describing innovative behaviour of individual firms. One increasingly
popular type of data are Literature-based Innovation Output (LBIO) data. These are compiled by screening specialist trade
journals for new-product announcements. Notwithstanding the substantial advantages, the eligibility of LBIO data for innovation
research remains controversial. In this paper the merits of LBIO data are examined by means of comparative analysis. A newly
built LBIO database is systematically compared with the widely used Community Innovation Survey. It shows that both databases
identify similar innovators in terms of firm size, distribution across industries and degree of innovativeness: LBIO data
can be considered a fully fledged alternative to traditional innovation data, highly eligible for innovation research.
This paper examines general characteristics of African science from a quantitative ‘scientometric’ perspective. More specifically,
that of research outputs of Africa-based authors published in the scientific literature during the years 1980–2004, either
within the international journals representing ‘mainstream’ science, or within national and regional journals reflecting ‘indigenous
science’. As for the international journals, the findings derived from Thomson Scientific’s Citation Indexes show that while
Africa’s share in worldwide science has steadily declined, the share of international co-publications has increased very significantly,
whereas low levels of international citation impact persist. A case study of South African journals reveals the existence
of several journals that are not processed for these international databases but nonetheless show a distinctive citation impact
on international research communities.
The two Journal Citation Reports of the Science Citation Index 2004 and the Social Science Citation Index 2004 were combined in order to analyze and map journals
and specialties at the edges and in the overlap between the two databases. For journals which belong to the overlap (e.g.,
Scientometrics), the merger mainly enriches our insight into the structure which can be obtained from the two databases separately; but
in the case of scientific journals which are more marginal in either database, the combination can provide a new perspective
on the position and function of these journals (e.g., Environment and Planning B — Planning and Design). The combined database additionally enables us to map citation environments in terms of the various specialties comprehensively.
Using the vector-space model, visualizations are provided for specialties that are parts of the overlap (information science,
science & technology studies). On the basis of the resulting visualizations, “betweenness” — a measure from social network
analysis — is suggested as an indicator for measuring the interdisciplinarity of journals.