Search Results
Abstract
A sample of 1,483 publications, representative of the scholarly production of LIS faculty, was searched in Web of Science (WoS), Google, and Google Scholar. The median number of citations found through WoS was zero for all types of publications except book chapters; the median for Google Scholar ranged from 1 for print/subscription journal articles to 3 for books and book chapters. For Google the median number of citations ranged from 9 for conference papers to 41 for books. A sample of the web citations was examined and classified as representing intellectual or non-intellectual impact. Almost 92% of the citations identified through Google Scholar represented intellectual impact — primarily citations from journal articles. Bibliographic services (non-intellectual impact) were the largest single contributor of citations identified through Google. Open access journal articles attracted more web citations but the citations to print/subscription journal articles more often represented intellectual impact. In spite of problems with Google Scholar, it has the potential to provide useful data for research evaluation, especially in a field where rapid and fine-grained analysis is desirable.
Abstract
The purpose of this study is to map semiconductor literature by author co-citation analysis in order to highlight major subject specializations in semiconductors and identify authors and their relationships within these specialties and within the field. Forty-six of the most productive authors were included in the sample list. Author samples were gathered from the INSPEC database from 1978 to 1997. The relatively low author co-citation frequencies indicate that there is a low connection among authors who publish in semiconductor journals and big differences among authors' research areas. Six sets of authors with co-citation greater than 100 times are M. Cardona and G. Lucovsky; T. Ito and K. Kobayashi; M. Cardona and G. Abstreiter; A. Y. Cho and H. Morkoc; C. R. Abernathy and W. S. Hobson; H. Morkoc and I. Akasaki. The Pearson correlation coefficient of author co-citation varies widely, i.e., from -0.17 to 0.92. This shows that some authors with high positive correlations are related in certain ways and co-cited, while other authors with high negative correlations may be rarely or never related and co-cited. Cluster analysis and multi-dimensional scaling are employed to create two-dimensional maps of author relationships in the cross-citation networks. It is found that the authors fall fairly clearly into three clusters. The first cluster covers authors in physics and its applications. The authors in the second group are experts in electrical and electronic engineering. The third group includes specialists in materials science. Because of its interdisciplinary nature and diverse subjects, semiconductor literature lacks a strong group of core authors. The field consists of several specialties around a weak center.
Introduction and background A well-designed and comprehensive citation index for the Social Sciences and Humanities (SSH) has many potential uses, but has yet to be realised. A recent initiative in this direction is the so
Abstract
The purpose of this article is to find a model for the first-citation or response distribution. Starting from plausible assumptions, we derive differential equations, whose solutions yield the requested functions. In fact, we propose two different double exponential distributions as candidates to describe the first-citation process. We found that some real data are best fitted by the first of these models and other by the second. We further note that Gompertz' curve plays an important role in this second model. These models can be used to predict the total number of articles in a fixed group that will ever be cited. We conclude that further research is needed to find out when one of the two models is more appropriate than the other.
Abstract
This paper examines a number of the criticisms that citation analysis has been subjected to over the years. It is argued that many of these criticisms have been based on only limited examinations of data in particular contexts and it remains unclear how broadly applicable these problems are to research conducted at different levels of analysis, in specific field, and among various national data sets. Relevant evidence is provided from analysis of Australian and international data. Citation analysis is likely to be most reliable when data is aggregated and at the highly-cited end of the distribution. It is possible to make valid inferences about individual cases, although considerable caution should be used. Bibliometric measures should be viewed as a useful supplement to other research evaluation measures rather than as a replacement.
Abstract
As part of a larger project to investigate knowledge flows between fields of science, westudied the differences in speed of knowledge transfer within and across disciplines. The agedistribution of references in three selections of articles was analysed, including almost 800.000references in journal publications of the United Kingdom in 1992, 700.000 references inpublications of Germany in 1992, and more than 11 million references in the world total ofpublications in 1998.The rate of citing documented knowledge from other disciplines appears to differ sharplyamong disciplines. For most of the disciplines the same ratio's are found in the three data sets.Exceptions show interesting differences in the interdisciplinary nature of a field in a country. Wefind a general tendency of a citation delay in case of knowledge transfer between different fieldsof science: citations to work of the own discipline show less of a time lag than citations to work ina foreign discipline. Between disciplines typical differences in the speed of incorporatingknowledge from other disciplines are observed, which appear to be relatively independent of timeand place: for each discipline the same pattern is found in the three data sets. The disciplinespecific characteristics found in the speed of interdisciplinary knowledge transfer may be point ofdeparture for further investigations. Results may contribute to explanations of differences incitation rates of interdisciplinary research.
Abstract
For practical reasons, bibliographic databases can only contain a subset of the scientific literature. The ISI citation databases are designed to cover the highest impact scientific research journals as well as a few other sources chosen by the Institute for Scientific Information (ISI). Google Scholar also contains citation information, but includes a less quality controlled collection of publications from different types of web documents. We define Google Scholar unique citations as those retrieved by Google Scholar which are not in the ISI database. We took a sample of 882 articles from 39 open access ISI-indexed journals in 2001 from biology, chemistry, physics and computing and classified the type, language, publication year and accessibility of the Google Scholar unique citing sources. The majority of Google Scholar unique citations (70%) were from full-text sources and there were large disciplinary differences between types of citing documents, suggesting that a wide range of non-ISI citing sources, especially from non-journal documents, are accessible by Google Scholar. This might be considered to be an advantage of Google Scholar, since it could be useful for citation tracking in a wider range of open access scholarly documents and to give a broader type of citation impact. An important corollary from our study is that Google Scholar’s wider coverage of Open Access (OA) web documents is likely to give a boost to the impact of OA research and the OA movement.
Abstract
Simple quantitative indices of pair-wise journal citation relatedness (based on the numbers of references given to and received from a journal title, which are provided by Science Citation Index database) are translated by an automatic clustering procedure into a meaningful map diagram reflecting topical relatedness of journals within a field of science. Such a map for 60 journals in marine and freshwater biology and related sciences published in 1987 reveals a tight cluster of marine biology journals quite distinct from the freshwater biology journal cluster and from the fisheries cluster. The journals within the marine biology cluster and those with strongest pair-wise links with them can be regarded as the core journals in marine biology. Indices of unilateral citation relatedness are used to obtain diagrams, which we term citograms. The citograms visualize patterns of citation relatedness of a journal (its citing and being cited). Journal self-citation can be meaningfully estimated using the bilateral index of relatedness. Self-citation is high in specialized or regional journal titles. It also appears to be quite substantial in journals of broader scope, which possibly reflect authors' subjective preferences.
Abstract
In his article 
networks of Scientific Papers
,Price argued that the N-rays reference network exhibits characteristics one would expect for a cumulative and rapidly developing research area. Although subsequent researchers have questioned Price's characterization of the N-rays network, there have been no replications of Price's work for either the N-rays literature or for any other literature. We reexamine the N-rays reference network, this time distinguishing negative citations and self citations from other citations. Although previous studies of negative and self citations show they are relatively infrequent in scientific literatures, we find that both are very prominent in the N-rays literature. In addition, we show that self citations comprise most of the recency effect observed in the N-rays reference network, and that the high level of self citations in the N-rays literature results primarily from the character of the journal that published the majority of the N-rays papers. Our findings therefore support those who have been skeptical about Price's claim that the N-rays reference graph exemplifies basic characteristics of the structure of scientific literatures.
Abstract
The Western European science policy establishment often claims that US articles are more frequently cited than articles of the European Union's scientists because they are published in journals with a large number of US publications and that these journals are forming the ‘core’ of the SCI. For the disciplines covered by the SCI, no significant correlation has been found between the ratio of the average number of citations per publication for publications with at least one EU address and at least one US address, respectively, on the one hand, and, on the other hand, the ratio of the corresponding number of publications per journal.
