Search (137 results, page 1 of 7)

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Content

Vgl. unter: https://www.leibniz-science20.de%2Fforschung%2Fprojekte%2Faltmetrics-in-verschiedenen-wissenschaftsdisziplinen%2F&ei=2jTgVaaXGcK4Udj1qdgB&usg=AFQjCNFOPdONj4RKBDf9YDJOLuz3lkGYlg&sig2=5YI3KWIGxBmk5_kv0P_8iQ.

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Abstract

The reference lists of forty-three education dissertations on curriculum and instruction completed at the University of Minnesota during the calendar years 2000-2002 were analyzed to inform collection development. As one measure of use of the academic library collection, the citation analysis yielded data to guide journal selection, retention, and cancellation decisions. The project aimed to ensure that the most frequently cited journals were retained on subscription. The serial monograph ratio for citation also was evaluated in comparison with other studies and explored in the context of funding ratios. Results of citation studies can provide a basis for liaison conversations with faculty in addition to guiding selection decisions. This research project can serve as a model for similar projects in other libraries that look at literature in education as well as other fields.

Date

10. 9.2000 17:38:22

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Abstract

Examines the use of networked information sources in scholarly communication. Networked information sources are defined broadly to cover: documents and images stored on electronic network hosts; data files; newsgroups; listservs; online information services and electronic periodicals. Reports results of a survey to determine how heavily, if at all, networked information sources are cited in scholarly printed periodicals published in 1993 and 1994. 27 printed periodicals, representing a wide range of subjects and the most influential periodicals in their fields, were identified through the Science Citation Index and Social Science Citation Index Journal Citation Reports. 97 articles were selected for further review and references, footnotes and bibliographies were checked for references to networked information sources. Only 2 articles were found to contain such references. Concludes that, although networked information sources facilitate scholars' work to a great extent during the research process, scholars have yet to incorporate such sources in the bibliographies of their published articles

Source

IFLA journal. 22(1996) no.3, S.240-245

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Abstract

This article reports research an analyzing and visualizing the impact of governmental funding an the amount and citation counts of research publications. For the first time, grant and publication data appear interlinked in one map. We start with an overview of related work and a discussion of available techniques. A concrete example- grant and publication data from Behavioral and Social Science Research, one of four extramural research programs at the National Institute an Aging (NIA)-is analyzed and visualized using the Vxlnsight® visualization tool. The analysis also illustrates current existing problems related to the quality and existence of data, data analysis, and processing. The article concludes with a list of recommendations an how to improve the quality of grant-publication maps and a discussion of research challenges for indicator-assisted evaluation and funding of research.

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Abstract

Assignability of authors to Web pages using either normal browsing procedures or browsing assisted by simple automatic extraction was investigated. Candidate strings for 1000 pages were extracted automatically from title elements, meta-tags, and address-like and copyright-like passages; 539 of the pages produced at least one candidate: 310 candidates from titles, 66 from meta-tags, 91 from address-like passages, and 259 from copyright-like passages. An assistant attempted to identify personal authors for 943 pages by examining the pages themselves and related pages; this added 90 pages with authors to the pages from which no candidate strings were extracted. Specific problems are noted and some refinements to the extraction methods are suggested.

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Abstract

States that it can be shown that claims of a lack of theories of citation are also indicative of a great need for a theory which links science dynamics and measurement. There is a wide gap between qualitative (science dynamics) and quantitative (measurement) approaches. To link them, proposes the use of the citation system, that potentially bridges a gap between measurement and epistemology, by applying system theory to the publication system

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Abstract

Thomson Reuters's Web of Science (WoS) began systematically collecting acknowledgment information in August 2008. Since then, bibliometric analysis of funding acknowledgment (FA) has been growing and has aroused intense interest and attention from both academia and policy makers. Examining the distribution of FA by citation index database, by language, and by acknowledgment type, we noted coverage limitations and potential biases in each analysis. We argue that despite its great value, bibliometric analysis of FA should be used with caution.

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Abstract

Using Web of Science data, portfolio analysis in terms of journal coverage can be projected onto a base map for units of analysis such as countries, cities, universities, and firms. The units of analysis under study can be compared statistically across the 10,000+ journals. The interdisciplinarity of the portfolios is measured using Rao-Stirling diversity or Zhang et?al.'s improved measure 2D3. At the country level we find regional differentiation (e.g., Latin American or Asian countries), but also a major divide between advanced and less-developed countries. Israel and Israeli cities outperform other nations and cities in terms of diversity. Universities appear to be specifically related to firms when a number of these units are exploratively compared. The instrument is relatively simple and straightforward, and one can generalize the application to any document set retrieved from the Web of Science (WoS). Further instruction is provided online at http://www.leydesdorff.net/portfolio.

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Abstract

Multidimensional data analysis or On-line analytical processing (OLAP) offers a single subject-oriented source for analyzing summary data based an various dimensions. We demonstrate that the OLAP approach gives a promising starting point for advanced analysis and comparison among summary data in informetrics applications. At the moment there is no single precise, commonly accepted logical/conceptual model for multidimensional analysis. This is because the requirements of applications vary considerably. We develop a conceptual/logical multidimensional model for supporting the complex and unpredictable needs of informetrics. Summary data are considered with respect of some dimensions. By changing dimensions the user may construct other views an the same summary data. We develop a multidimensional query language whose basic idea is to support the definition of views in a way, which is natural and intuitive for lay users in the informetrics area. We show that this view-oriented query language has a great expressive power and its degree of declarativity is greater than in contemporary operation-oriented or SQL (Structured Query Language)-like OLAP query languages.

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Abstract

The greatest number of open access journals (OAJs) is found in the sciences and their influence is growing. However, there are only a few studies on the acceptance and thereby integration of these OAJs in the scholarly communication system. Even fewer studies provide insight into the differences across disciplines. This study is an analysis of the citing behaviour in journals within three science fields: biology, mathematics, and pharmacy and pharmacology. It is a statistical analysis of OAJs as well as non-OAJs including both the citing and cited side of the journal to journal citations. The multivariate linear regression reveals many similarities in citing behaviour across fields and media. But it also points to great differences in the integration of OAJs. The integration of OAJs in the scholarly communication system varies considerably across fields. The implications for bibliometric research are discussed.

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Abstract

Characteristics of the Journal of the American Society for Information Science and Technology and 76 other journals listed in the InformationSystems category of the Journal Citation Reports-Science edition 2009 were analyzed. Besides reporting usual bibliographic indicators, we investigated the human cornerstone of any peer-reviewed journal: its editorial board. Demographic data about the 2,846 gatekeepers serving in information systems (IS) editorial boards were collected. We discuss various scientometric indicators supported by descriptive statistics. Our findings reflect the great variety of IS journals in terms of research output, author communities, editorial boards, and gatekeeper demographics (e.g., diversity in gender and location), seniority, authority, and degree of involvement in editorial boards. We believe that these results may help the general public and scholars (e.g., readers, authors, journal gatekeepers, policy makers) to revise and increase their knowledge of scholarly communication in the IS field. The EB_IS_2009 dataset supporting this scientometric study is released as online supplementary material to this article to foster further research on editorial boards.

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Abstract

Twitter provides a channel of collecting and publishing instant information on major events like natural disasters. However, information flow on Twitter is of great volume. For a specific event, messages collected from the Twitter Stream based on either location constraint or predefined keywords would contain a lot of noise. In this article, we propose a method to achieve both high-precision and high-recall in collecting event-related tweets. Our method involves an automatic keyword generation component, and an event-related tweet identification component. For keyword generation, we consider three properties of candidate keywords, namely relevance, coverage, and evolvement. The keyword updating mechanism enables our method to track the main topics of tweets along event development. To minimize annotation effort in identifying event-related tweets, we adopt active learning and incorporate multiple-instance learning which assigns labels to bags instead of instances (that is, individual tweets). Through experiments on two real-world events, we demonstrate the superiority of our method against state-of-the-art alternatives.

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Abstract

In one of two bibliometric papers in this issue Brown looks at formal publication and citation of Eprints as shown by the policies and practices of 37 top tier physics journals, and by citation trends in ISI's SciSearch database and Journal Citation Reports. Citation analysis was carried out if Eprint cites were indicated by editor response, instruction to authors sections, reports in the literature, or actual examination of citation lists. Total contribution to 12 archives and their citation counts in the journals were compiled. Of the 13 editors surveyed that responded, 8 published papers that had appeared in the archive. Two of these required removal from the archive at publication; two of the 13 did not publish papers that have appeared as Eprints. A review journal that solicits its contributions allowed citation of Eprints. Seven allowed citations to Eprints, but were less than enthusiastic.Nearly 36,000 citations were made to the 12 archives. Citations to the 37 journals and their impact factors remain constant over the period of 1991 to 1998. Eprint citations appear to peak about 3 years after appearance as do citations to published papers. Contribution to the archives, and their use as measured by citation, is clearly growing. Citation form and publishing policy varies from journal to journal.

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Abstract

Webometrics, the quantitative study of Web-related phenomena, emerged from the realization that methods originally designed for bibliometric analysis of scientific journal article citation patterns could be applied to the Web, with commercial search engines providing the raw data. Almind and Ingwersen (1997) defined the field and gave it its name. Other pioneers included Rodriguez Gairin (1997) and Aguillo (1998). Larson (1996) undertook exploratory link structure analysis, as did Rousseau (1997). Webometrics encompasses research from fields beyond information science such as communication studies, statistical physics, and computer science. In this review we concentrate on link analysis, but also cover other aspects of webometrics, including Web log fle analysis. One theme that runs through this chapter is the messiness of Web data and the need for data cleansing heuristics. The uncontrolled Web creates numerous problems in the interpretation of results, for instance, from the automatic creation or replication of links. The loose connection between top-level domain specifications (e.g., com, edu, and org) and their actual content is also a frustrating problem. For example, many .com sites contain noncommercial content, although com is ostensibly the main commercial top-level domain. Indeed, a skeptical researcher could claim that obstacles of this kind are so great that all Web analyses lack value. As will be seen, one response to this view, a view shared by critics of evaluative bibliometrics, is to demonstrate that Web data correlate significantly with some non-Web data in order to prove that the Web data are not wholly random. A practical response has been to develop increasingly sophisticated data cleansing techniques and multiple data analysis methods.

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Abstract

A model is presented of the manifestation of the birth and development of a scientific specialty in a collection of journal papers. The proposed model, Cumulative Advantage by Paper with Exemplars (CAPE) is an adaptation of Price's cumulative advantage model (D. Price, 1976). Two modifications are made: (a) references are cited in groups by paper, and (b) the model accounts for the generation of highly cited exemplar references immediately after the birth of the specialty. This simple growth process mimics many characteristic features of real collections of papers, including the structure of the paper-to-reference matrix, the reference-per-paper distribution, the paper-per-reference distribution, the bibliographic coupling distribution, the cocitation distribution, the bibliographic coupling clustering coefficient distribution, and the temporal distribution of exemplar references. The model yields a great deal of insight into the process that produces the connectedness and clustering of a collection of articles and references. Two examples are presented and successfully modeled: a collection of 131 articles an MEMS RF (microelectromechnical systems radio frequency) switches, and a collection of 901 articles an the subject of complex networks.

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Abstract

Purpose - This paper offers a practical insight into the application of Lotka's law of author productivity to the question of how likely it is that an author will return to a particular publisher (rather than make another contribution to a subject literature, which is its usual application). The question of author loyalty, especially repeat visits, is one which is of great interest to publishers. Design/methodology/approach - This paper shows, possibly for the first time, that the author productivity distribution predicted by Lotka's law for subject literatures also holds for publisher aggregates, in this case, all Emerald authors. Findings - The ideas presented here are speculative and programmatic: they raise questions and provide a robust intellectual framework for further research into the determinants of author loyalty, as seen from the publisher side. Practical implications - The implications for commissioning editors and marketing departments in journal publishing houses are that repeat visiting authors are indeed scarce commodities, not necessarily because of barriers put in their way by publishers, but because research production is very asymmetrically skewed in favour of a small productive élite. Originality/value - By analysing survey data it should be possible, within very broad parameters, to identify clusters of say high, medium and low research activity authors. This would provide insight into potential "hot spots" of future publishing intent and, in the case of dense and overworked research areas, early warning as to when to start looking elsewhere for future articles.

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Abstract

We use a technique recently developed by V. Blondel, J.-L. Guillaume, R. Lambiotte, and E. Lefebvre (2008) to detect scientific specialties from author cocitation networks. This algorithm has distinct advantages over most previous methods used to obtain cocitation clusters since it avoids the use of similarity measures, relies entirely on the topology of the weighted network, and can be applied to relatively large networks. Most importantly, it requires no subjective interpretation of the cocitation data or of the communities found. Using two examples, we show that the resulting specialties are the smallest coherent groups of researchers (within a hierarchy of cluster sizes) and can thus be identified unambiguously. Furthermore, we confirm that these communities are indeed representative of what we know about the structure of a given scientific discipline and that as specialties, they can be accurately characterized by a few keywords (from the publication titles). We argue that this robust and efficient algorithm is particularly well-suited to cocitation networks and that the results generated can be of great use to researchers studying various facets of the structure and evolution of science.

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Abstract

Thomson Reuters' Web of Science (WoS) is undoubtedly a great tool for scientiometrics purposes. It allows one to retrieve and compute different measures such as the total number of papers that satisfy a particular condition; however, it also is well known that this tool imposes several different restrictions that make obtaining certain results difficult. One of those constraints is that the tool does not offer the total count of documents in a dataset if it is larger than 100,000 items. In this article, we propose and analyze different approaches that involve partitioning the search space (using the Source field) to retrieve item counts for very large datasets from the WoS. The proposed techniques improve previous approaches: They do not need any extra information about the retrieved dataset (thus allowing completely automatic procedures to retrieve the results), they are designed to avoid many of the restrictions imposed by the WoS, and they can be easily applied to almost any query. Finally, a description of WoS Query Partitioner, a freely available and online interactive tool that implements those techniques, is presented.

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Abstract

How can citation analysis take into account the highly collaborative nature and unique research and publication culture of biomedical research fields? This study explores this question by introducing last-author citation counting and comparing it with traditional first-author counting and theoretically optimal all-author counting in the stem cell research field for the years 2004-2009. For citation ranking, last-author counting, which is directly supported by Scopus but not by ISI databases, appears to approximate all-author counting quite well in a field where heads of research labs are traditionally listed as last authors; however, first author counting does not. For field mapping, we find that author co-citation analyses based on different counting methods all produce similar overall intellectual structures of a research field, but detailed structures and minor specialties revealed differ to various degrees and thus require great caution to interpret. This is true especially when authors are selected into the analysis based on citedness, because author selection is found to have a greater effect on mapping results than does choice of co-citation counting method. Findings are based on a comprehensive, high-quality dataset extracted in several steps from PubMed and Scopus and subjected to automatic reference and author name disambiguation.

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Abstract

Just as citations to a book can be counted, so can that book's libcitations-the number of libraries in a consortium that hold it. These holdings counts per title can be obtained from the consortium's union catalog, such as OCLC's WorldCat. Librarians seeking to serve their customers well must be attuned to various kinds of merit in books. The result in WorldCat is a great variation in the libcitations particular books receive. The higher a title's count (or percentile), the more famous it is-either absolutely or within a subject class. Degree of fame also indicates cultural impact, allowing that further documentation of impact may be needed. Using WorldCat data, we illustrate high, medium, and low degrees of fame with 170 titles published during 1990-1995 or 2001-2006 and spanning the 10 main Dewey classes. We use their total libcitation counts or their counts from members of the Association of Research Libraries, or both, as of late 2011. Our analysis of their fame draws on the recognizability of their authors, the extent to which they and their authors are covered by Wikipedia, and whether they have movie or TV versions. Ordinal scales based on Wikipedia coverage and on libcitation counts are very significantly associated.