lack of credibility of information on the Internet. Students and researchers are not able to make a distinction between electronic resources and traditional scholarly resources (Tenopir 2003 ). To help students and researchers evaluate the quality of
, traditional citation-based bibliometric quantitative methods have been widely used to evaluate scholarly impact at individual, departmental, university and national levels for over five decades (Moed 2005 ). However, citation analysis is limited by the
Science models usually address issues in statistical modeling and mapping of structures and scholarly activities in science. As a further dimension, that should be considered in science modeling as well, the paper
Relationships between age and scholarly impact were assessed by determining the number of times single-author articles (N=227) published inPsychological Review between 1965 and 1980 were cited in the fifth year following publication. There were substantial individual differences in citation rates, but this measure of scholarly impact did not correlate with either the chronological age of authors or their professional age (years since PhD award). Although the majority of articles inPsychological Review were published by authors under the age of 40, such a bias is to be expected in terms of the age distribution of American psychologists. When allowance was made for the number of authors in different age ranges, older authors were no less likely than younger authors to have generated a high-impact article (an article cited 10 or more times in the fifth year after publication). The data offer no support to claims that publications by young scientists have greater impact.
radical political change has led to the commencement of broad social, economic and cultural transformations, which are generally signified in scholarly literature as post-socialist “transitions” ( Hann 2004 :1). Those processes inevitably affected politics
given to the logically-prior conceptual issue of what the theoretically ideal summary bibliometric measure would look like. Citations are clearly only of interest as an observable indicator for a latent, but more important, concept of “scholarly
The purpose of this paper was to analyze the intellectual structure of biomedical informatics reflected in scholarly events
such as conferences, workshops, symposia, and seminars. As analysis variables, ‘call for paper topics’, ‘session titles’ and
author keywords from biomedical informatics-related scholarly events, and the MeSH descriptors were combined. As analysis
cases, the titles and abstracts of 12,536 papers presented at five medical informatics (MI) and six bioinformatics (BI) global
scale scholarly event series during the years 1999–2008 were collected. Then, n-gram terms (MI = 6,958; BI = 5,436) from the paper corpus were extracted and the term co-occurrence network was analyzed.
One hundred important topics for each medical informatics and bioinformatics were identified through the hub-authority metric,
and their usage contexts were compared with the k-nearest neighbor measure. To research trends, newly popular topics by 2-year
period units were observed. In the past 10 years the most important topic in MI has been “decision support”, while in BI “gene
expression”. Though the two communities share several methodologies, according to our analysis, they do not use them in the
same context. This evidence suggests that MI uses technologies for the improvement of productivity in clinical settings, while
BI uses algorithms as its tools for scientific biological discovery. Though MI and BI are arguably separate research fields,
their topics are increasingly intertwined, and the gap between the fields blurred, forming a broad informatics—namely biomedical
informatics. Using scholarly events as data sources for domain analysis is the closest way to approximate the forefront of
A bibliometric analysis was performed on a set of 1718 documents relating to Web 2.0 to explore the dimensions and characteristics
of this emerging field. It has been found that Web 2.0 has its root deep in social networks with medicine and sociology as
the major contributing disciplines to the scholarly publications beyond its technology backbone — information and computer
science. Terms germane to Web 2.0, extracted from the data collected in this study, were also visualized to reflect the very
nature of this rising star on the Internet. Web 2.0, according to the current research, is of the user, by the user, and more
importantly, for the user.
Using a dataset of refereed conference papers, this work explores the determinants of academic production in the field of
management. The estimation of a count data model shows that the countries’ level of economic development and their economy
size have a positive and highly significant effect on scholarly management knowledge production. The linguistic variable (English
as official language), which has been cited by the literature as an important factor facilitating the participation in the
international scientific arena, has also a positive and statistically significant effect.