Search (34 results, page 1 of 2)

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Abstract

This article discusses the rationale for creating historiographs of scholarly topics using a new program called HistCite(TM), which produces a variety of analyses to aid the historian identify key events (papers), people (authors), and journals in a field. By creating a genealogic profile of the evolution, the program aids the scholar in evaluating the paradigm involved.

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Abstract

Describes the construction of improved informetric models of individual scientific and technological areas on the basis of individual co citation clusters. The developed methodology of replenishment of research front with accidently absent papers describes the model more completely. Proposes the simple method of cluster 'dynamization' for the study of evolution of research area. The transition under consideration from co citation clusters to lexical maps of papers and patents enables the monitoring of the relationshuip between R and D in a given technological area. Provides the example from modern chemical engineering of Pressure-Swing Adsorption

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Abstract

Provides a synoptic review and history of citation indexes and their evolution into research evaluation tools including a discussion of the use of bibliometric data for evaluating US institutions (academic departments) by the National Research Council (NRC). Covers the origin and uses of periodical impact factors, validation studies of citation analysis, information retrieval and dissemination (current awareness), citation consciousness, historiography and science mapping, Citation Classics, and the history of contemporary science. Illustrates the retrieval of information by cited reference searching, especially as it applies to avoiding duplicated research. Discusses the 15 year cumulative impacts of periodicals and the percentage of uncitedness, the emergence of scientometrics, old boy networks, and citation frequency distributions. Concludes with observations about the future of citation indexing

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Abstract

The construction of virtual science landscapes based on citation networks and the strategic use of the information therein shed new light on the issues of the evolution of the science system and possibilities for control. Leydesdorff's approach to citation theory described in his 1998 article (see this issue of LISA) takes into account the dual layered character of communication networks and the second order nature of the science system. This perspective may help to sharpen the awareness of scientists and science policy makers for possible feedback loops within actions and activities in the science system, and probably nonlinear phenomena resulting therefrom. Sketches an additional link to geometrically oriented evolutionary theories and uses a specific landscape concept as a framework for some comments

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Abstract

Citations support the communication of specialist knowledge by allowing authors and readers to make specific selections in several contexts at the same time. In the interactions between the social network of authors and the network of their reflexive communications, a sub textual code of communication with a distributed character has emerged. Citation analysis reflects on citation practices. Reference lists are aggregated in scientometric analysis using one of the available contexts to reduce the complexity: geometrical representations of dynamic operations are reflected in corresponding theories of citation. The specific contexts represented in the modern citation can be deconstructed from the perspective of the cultural evolution of scientific communication

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Abstract

Citation-chasing is proposed as a method of discovering additional terms to enhance subjectsearch retrieval. Subjects attached to OCLC records for cited works are compared to those attached to original citing sources. Citing sources were produced via a subject-list search in a library catalog using the LCSH "Language and languages-Origin." A subject-search was employed to avoid subjectivity in choosing sources. References from the sources were searched in OCLC where applicable, and the subject headings were retrieved. The subjects were ranked by citation-frequency and tiered into 3 groups in a Bradford-like distribution. Highly cited subjects were produced that were not revealed through the original search. A difference in relative importance among the subjects was also revealed. Broad extra-linguistic topics like evolution are more prominent than specific linguistic topics like phonology. There are exceptions, which appear somewhat predictable by the amount of imbalance in citation-representation among the 2 sources. Citation leaders were also produced for authors and secondary-source titles.

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Abstract

We present evidence that in some research fields, research published in journals and reported on the Web may collectively represent different evolutionary stages of the field, with journals lagging a few years behind the Web on average, and that a "two-tier" scholarly communication system may therefore be evolving. We conclude that in such fields, (a) for detecting current research fronts, author co-citation analyses (ACA) using articles published on the Web as a data source can outperform traditional ACAs using articles published in journals as data, and that (b) as a result, it is important to use multiple data sources in citation analysis studies of scholarly communication for a complete picture of communication patterns. Our evidence stems from comparing the respective intellectual structures of the XML research field, a subfield of computer science, as revealed from three sets of ACA covering two time periods: (a) from the field's beginnings in 1996 to 2001, and (b) from 2001 to 2006. For the first time period, we analyze research articles both from journals as indexed by the Science Citation Index (SCI) and from the Web as indexed by CiteSeer. We follow up by an ACA of SCI data for the second time period. We find that most trends in the evolution of this field from the first to the second time period that we find when comparing ACA results from the SCI between the two time periods already were apparent in the ACA results from CiteSeer during the first time period.

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Abstract

The paper proposes a new approach to create a patent classification system to replace the IPC or UPC system for conducting patent analysis and management. The new approach is based on co-citation analysis of bibliometrics. The traditional approach for management of patents, which is based on either the IPC or UPC, is too general to meet the needs of specific industries. In addition, some patents are placed in incorrect categories, making it difficult for enterprises to carry out R&D planning, technology positioning, patent strategy-making and technology forecasting. Therefore, it is essential to develop a patent classification system that is adaptive to the characteristics of a specific industry. The analysis of this approach is divided into three phases. Phase I selects appropriate databases to conduct patent searches according to the subject and objective of this study and then select basic patents. Phase II uses the co-cited frequency of the basic patent pairs to assess their similarity. Phase III uses factor analysis to establish a classification system and assess the efficiency of the proposed approach. The main contribution of this approach is to develop a patent classification system based on patent similarities to assist patent manager in understanding the basic patents for a specific industry, the relationships among categories of technologies and the evolution of a technology category.

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Abstract

Previous analyses identified research on environmental tobacco smoke to be subject to strong fluctuations as measured by both quantitative and qualitative indicators. The evolution of search algorithms (based on the Web of Science and Web of Knowledge database platforms) was used to show the impact of errors of omission and commission in the outcomes of scientometric research. Optimization of the search algorithm led to the complete reassessment of previously published findings on the performance of environmental tobacco smoke research. Instead of strong continuous growth, the field of environmental tobacco smoke research was shown to experience stagnation or slow growth since mid-1990s when evaluated quantitatively. Qualitative analysis revealed steady but slow increase in the citation rate and decrease in uncitedness. Country analysis revealed the North-European countries as leaders in environmental tobacco smoke research (when the normalized results were evaluated both quantitatively and qualitatively), whereas the United States ranked first only when assessing the total number of papers produced. Scientometric research artifacts, including both errors of omission and commission, were shown to be capable of completely obscuring the real output of the chosen research field.

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Abstract

Main path analysis is a popular method for extracting the scientific backbone from the citation network of a research domain. Existing approaches ignored the semantic relationships between the citing and cited publications, resulting in several adverse issues, in terms of coherence of main paths and coverage of significant studies. This paper advocated the semantic main path network analysis approach to alleviate these issues based on citation function analysis. A wide variety of SciBERT-based deep learning models were designed for identifying citation functions. Semantic citation networks were built by either including important citations, for example, extension, motivation, usage and similarity, or excluding incidental citations like background and future work. Semantic main path network was built by merging the top-K main paths extracted from various time slices of semantic citation network. In addition, a three-way framework was proposed for the quantitative evaluation of main path analysis results. Both qualitative and quantitative analysis on three research areas of computational linguistics demonstrated that, compared to semantics-agnostic counterparts, different types of semantic main path networks provide complementary views of scientific knowledge flows. Combining them together, we obtained a more precise and comprehensive picture of domain evolution and uncover more coherent development pathways between scientific ideas.

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Abstract

Die Szientometrie beschäftigt sich mit der Messbarkeit wissenschaftlicher Leistungen anhand bibliothekarisch nachweisbarer Publikationsergebnisse. Bei genauer Betrachtung ist es ihr Ziel, die Wissenszunahme der Wissenschaft zu messen. Die wissenschaftliche Produktion in Form von Publikationen wächst seit über dreihundert Jahren konstant mit ca. 3,5% pro Jahr. Das entspricht einerVerdopplungsrate von 20 Jahren, die zuerst dem Bibliothekar Fremont Rider 1948 bei Büchern auffiel und die 1963 von Derek J. de Solla Price auch für das Wachstum von Zeitschriften und Bibliografien bestätigt wurde. Die Konstanz dieser Evolution, unabhängig aller sich ereignenden Katastrophen, ist nur zum Teil verstanden, macht aber den unaufhaltsamen Fortschritt der Wissenschaft deutlich. Alle 20 Jahre wird so viel publiziert wie in allen Jahrhunderten davor. Eine etwa gleiche Zunahme verzeichnen die Wissenschaftler, die damit etwa gleich produktiv bleiben. Von ihnen allen sind damit ca. 87% unsere heutigen Zeitgenossen. Aus diesem Wachstum heraus können wir abschätzen, dass in 100.000 laufenden Zeitschriften heute etwa 10 Mio. Publikationen jährlich erscheinen, die von 10 Mio. Wissenschaftlern verfasst werden. Dabei definieren sich nur die als Wissenschaftler, die durchschnittlich eine Publikation jährlich verfassen. Die gesamte Produktion an Buchtiteln, die bisher erschien, dürfte bei etwa 100 Mio. liegen. Davon sind etwa 20 Mio. als wissenschaftlich einzustufen. Wenn folglich 87% aller Wissenschaftler noch heute leben, so betrug die Gesamtzahl der Wissenschaftler in der Welt bisher 11,5 Mio., die in ihrem Leben durchschnittlich 1,5 Bücher pro Kopf verfassten, und etwa das 10-20fache an Zeitschriftenbeiträgen leisteten. Ein Teil dieser Bücher sind allerdings Neuauflagen und Übersetzungen. Nach Lotka, A. J. ist die Produktivität der Wissenschaftler eine schiefe Verteilung von der Form A/n**2, wobei A die Zahl der Autoren mit nur einer Publikation ist und n die Publikationen pro Autor. Während Price in seinen "Networks of Scientific Papers" Vergleichswerte von n**2,5 bis n**3 angab, zeigten Untersuchungen am Science Citation Index (SCI), die auf die gesamte naturwissenschaftliche Literatur hochgerechnet wurden, eher einen Wert von n**1,7. Auf die Tatsache, dass eine Verdopplungsrate der Wissenschaftler von 20 Jahren und eine solche der Menschheit von etwa 50 Jahren dazu führt, dass eines Tages alle Menschen Wissenschaftler werden, hat Price bereits 1963 hingewiesen. Dieser Zustand müsste bei 10 Mio. Wissenschaftlern und 6 Mrd. Menschen in etwa 300 Jahren eintreten, ein nur scheinbar absurder Gedanke, wenn man bedenkt, dass man sich vor 300 Jahren auch kaum vorstellen konnte, dass alle Menschen Lesen, Schreiben und Rechnen lernen können, und dass wir uns ungebildete Menschen immer weniger leisten können.

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Abstract

This article explores the status of research in hydrogeology using data mining techniques. First we try to explain what citation analysis is and review some of the previous work on citation analysis. The main idea in this article is to address some common issues about citation numbers and the use of these data. To validate the use of citation numbers, we compare the citation patterns for Water Resources Research papers in the 1980s with those in the 1990s. The citation growths for highly cited authors from the 1980s are used to examine whether it is possible to predict the citation patterns for highly-cited authors in the 1990s. If the citation data prove to be steady and stable, these numbers then can be used to explore the evolution of science in hydrogeology. The famous quotation, "If you are not the lead dog, the scenery never changes," attributed to Lee Iacocca, points to the importance of an entrepreneurial spirit in all forms of endeavor. In the case of hydrogeological research, impact analysis makes it clear how important it is to be a pioneer. Statistical correlation coefficients are used to retrieve papers among a collection of 2,847 papers before and after 1991 sharing the same topics with 273 papers in 1991 in Water Resources Research. The numbers of papers before and after 1991 are then plotted against various levels of citations for papers in 1991 to compare the distributions of paper population before and after that year. The similarity metrics based on word counts can ensure that the "before" papers are like ancestors and "after" papers are descendants in the same type of research. This exercise gives us an idea of how many papers are populated before and after 1991 (1991 is chosen based on balanced numbers of papers before and after that year). In addition, the impact of papers is measured in terms of citation presented as "percentile," a relative measure based on rankings in one year, in order to minimize the effect of time.

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Date

13. 7.2008 19:53:22

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Date

7. 2.2005 14:10:22

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Date

22. 7.2006 15:22:28

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Source

Password. 2002, H.6, S.22-25

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Date

22. 3.2009 19:22:35

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Date

17.12.2013 11:02:22