Search (158 results, page 1 of 8)

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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

This study investigated name changes of women authors to determine how they were represented in indexes and cited references and identify problem areas. A secondary purpose of the study was to investigate whether or not indexing services were using authority control and how this influenced the search results. The works of eight library science authors who had published under multiple names were examined. The researchers compared author names as they appeared on title pages of publications versus in four online databases and in bibliographies by checking 380 publications and 1,159 citations. Author names were correctly provided 81.22% of the time in indexing services and 90.94% in citation lists. The lowest accuracy (54.55%) occurred when limiting to publications found in Library Literature. The highest accuracy (94.18%) occurred with works published before a surname changed. Author names in indexes and citations correctly matched names on journal articles more often than for any other type of publication. Indexes and citation style manuals treated author names in multiple ways, often altering names substantially from how they appear on the title page. Recommendations are made for changes in editorial styles by indexing services and by the authors themselves to help alleviate future confusion in author name searching.

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Abstract

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.

Date

22. 3.2009 17:49:11

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Abstract

Compared to previous studies that generally detect scientific breakthroughs based on citation patterns, this article proposes a knowledge entity-based disruption indicator by quantifying the change of knowledge directly created and inspired by scientific breakthroughs to their evolutionary trajectories. Two groups of analytic units, including MeSH terms and their co-occurrences, are employed independently by the indicator to measure the change of knowledge. The effectiveness of the proposed indicators was evaluated against the four datasets of scientific breakthroughs derived from four recognition trials. In terms of identifying scientific breakthroughs, the proposed disruption indicator based on MeSH co-occurrences outperforms that based on MeSH terms and three earlier citation-based disruption indicators. It is also shown that in our indicator, measuring the change of knowledge inspired by the focal paper in its evolutionary trajectory is a larger contributor than measuring the change created by the focal paper. Our study not only offers empirical insights into conceptual understanding of scientific breakthroughs but also provides practical disruption indicator for scientists and science management agencies searching for valuable research.

Date

22. 1.2023 18:37:33

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Abstract

Purpose - The purpose of this paper is to analyze the disciplinary orientation of scientific publications that were mentioned on different social media platforms, focussing on their differences and similarities with citation counts. Design/methodology/approach - Social media metrics and readership counts, associated with 500,216 publications and their citation data from the Web of Science database, were collected from Altmetric.com and Mendeley. Results are presented through descriptive statistical analyses together with science maps generated with VOSviewer. Findings - The results confirm Mendeley as the most prevalent social media source with similar characteristics to citations in their distribution across fields and their density in average values per publication. The humanities, natural sciences, and engineering disciplines have a much lower presence of social media metrics. Twitter has a stronger focus on general medicine and social sciences. Other sources (blog, Facebook, Google+, and news media mentions) are more prominent in regards to multidisciplinary journals. Originality/value - This paper reinforces the relevance of Mendeley as a social media source for analytical purposes from a disciplinary perspective, being particularly relevant for the social sciences (together with Twitter). Key implications for the use of social media metrics on the evaluation of research performance (e.g. the concentration of some social media metrics, such as blogs, news items, etc., around multidisciplinary journals) are identified.

Date

20. 1.2015 18:30:22

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Abstract

Author searching is traditionally based on the matching of name strings. Special characteristics of authors as personal names and subject indicators are not considered. This makes it difficult to identify a set of related authors or to group authors by subjects in retrieval systems. In this paper, we describe the design and implementation of a prototype visualization system to enhance author searching. The system, called AuthorLink, is based on author co-citation analysis and visualization mapping algorithms such as Kohonen's feature maps and Pathfinder networks. AuthorLink produces interactive author maps in real time from a database of 1.26 million records supplied by the Institute for Scientific Information. The maps show subject groupings and more fine-grained intellectual connections among authors. Through the interactive interface the user can take advantage of such information to refine queries and retrieve documents through point-and-click manipulation of the authors' names.

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Abstract

Chemical Abstracts Service recently unveiled citation searching in Chemical Abstracts. With Chemical Abstracts and Science Citation Index both now available for citation searching, this study compares the duplication and uniqueness of citing references for works of chemistry researchers for the years 1999-2001. The two indexes cover very similar source material, so one would expect the citation results to be very similar. This analysis of SciFinder Scholar and Web of Science shows some important differences as the databases are currently offered. Authors and institutions using citation counts as measures of scientific productivity should take note.

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Abstract

A citation analysis examined the 28 best articles published in JASIS from 1969-1996. Best articles tend to single-authored works twice as long as the avergae article published in JASIS. They are cited and self-cited much more often than the average article. The greatest source of references made to the best articles is from JASIS itself. The top 5 best papers focus largely on information retrieval and online searching

Content

Top by numbers of citations: (1) Saracevic, T. et al.: A study of information seeking and retrieving I-III (1988); (2) Bates, M.: Information search tactics (1979); (3) Cooper, W.S.: On selecting a measure of retrieval effectiveness (1973); (4) Marcus, R.S.: A experimental comparison of the effectiveness of computers and humans as search intermediaries (1983); (4) Fidel, R.: Online searching styles (1984)

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Abstract

One of the solutions to help scientists filter the most relevant publications and, thus, to stay current on developments in their fields during the transition from "little science" to "big science", was the introduction of citation indexing as a Wellsian "World Brain" (Garfield, 1964) of scientific information: It is too much to expect a research worker to spend an inordinate amount of time searching for the bibliographic descendants of antecedent papers. It would not be excessive to demand that the thorough scholar check all papers that have cited or criticized such papers, if they could be located quickly. The citation index makes this check practicable (Garfield, 1955, p. 108). In retrospective, citation indexing can be perceived as a pre-social web version of crowdsourcing, as it is based on the concept that the community of citing authors outperforms indexers in highlighting cognitive links between papers, particularly on the level of specific ideas and concepts (Garfield, 1983). Over the last 50 years, citation analysis and more generally, bibliometric methods, have developed from information retrieval tools to research evaluation metrics, where they are presumed to make scientific funding more efficient and effective (Moed, 2006). However, the dominance of bibliometric indicators in research evaluation has also led to significant goal displacement (Merton, 1957) and the oversimplification of notions of "research productivity" and "scientific quality", creating adverse effects such as salami publishing, honorary authorships, citation cartels, and misuse of indicators (Binswanger, 2015; Cronin and Sugimoto, 2014; Frey and Osterloh, 2006; Haustein and Larivière, 2015; Weingart, 2005).

Date

20. 1.2015 18:30:22

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Abstract

Scientific information has stopped growing exponentially as in the last 300 years. Nevertheless, the number of scientific papers published yearly remains dramatic. Well orderd databases and sophisticated search systems allow scientists to find the needle in the haystack. A growing number of factual databases as well as more reviews compress and refine information. Not searching but controlling and working up information appear to become the most important problem in the future

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Abstract

Results in the literature concerning the probability that an author publishes r articles in time t are reexamined, and it is found that a negative binomial distribution bits scientific productivity data (by the chi-squared goodness-of-fit-test) better than many other distribution such as geometric, logarithmic, zeta, cumulative advantage, etc. It is shown analytically that the nagative binomial distribution describes a pattern of scientific productivity under the 'success-breeds-success' condition in a wide variety of social circumstances

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Abstract

Finding relevant publications is a common task. Typically, a researcher browses through a list of publications and traces additional relevant publications. When relevant publications are identified, the list may be expanded by the citation links of the relevant publications. The information needs of researchers may change as they go through such iterative processes. The exploration process quickly becomes cumbersome as the list expands. Most existing academic search systems tend to be limited in terms of the extent to which searchers can adapt their search as they proceed. In this article, we introduce an adaptive visual exploration system named PaperPoles to support exploration of scientific publications in a context-aware environment. Searchers can express their information needs by intuitively formulating positive and negative queries. The search results are grouped and displayed in a cluster view, which shows aspects and relevance patterns of the results to support navigation and exploration. We conducted an experiment to compare PaperPoles with a list-based interface in performing two academic search tasks with different complexity. The results show that PaperPoles can improve the accuracy of searching for the simple and complex tasks. It can also reduce the completion time of searching and improve exploration effectiveness in the complex task. PaperPoles demonstrates a potentially effective workflow for adaptive visual search of complex information.

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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

This article studies citation practices in the arts and humanities from a theoretical and conceptual viewpoint, drawing on studies from fields like linguistics, history, library & information science, and the sociology of science. The use of references in the humanities is discussed in connection with the growing interest in the possibilities of applying citation analysis to humanistic disciplines. The study shows how the use of references within the humanities is connected to concepts of originality, to intellectual organization, and to searching and writing. Finally, it is acknowledged that the use of references is connected to stylistic, epistemological, and organizational differences, and these differences must be taken into account when applying citation analysis to humanistic disciplines.

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Abstract

In single-authored bibliographies only single scientist distribution can be found. But in multi-authored bibliographies single scientists distribution, pairs distribution, triples distribution, etc., can be presented. Whereas regarding Lotka's law single scientists P distribution (both in single-authored and in multi-authored bibliographies) is of interest, in the future pairs P, Q distribution, triples P, Q, R distribution, etc. should be considered Starting with pair distribution, the following question arises in the present paper: Is there also any regularity or well-ordered structure for the distribution of coauthor pairs in journals in analogy to Lotka's law for the distribution of single authors? Usually, in information science "laws " or "regularities " (for example Lotka's law) are mathematical descriptions of observed data inform of functions; however explanations of these phenomena are mostly missing. By contrast, in this paper the derivation of a formula for describing the distribution of the number of co-author pairs will be presented based on wellknown regularities in socio psychology or sociology in conjunction with the Gestalt theory as explanation for well-ordered collaboration structures and production of scientific literature, as well as derivations from Lotka's law. The assumed regularities for the distribution of co-author pairs in journals could be shown in the co-authorship data (1980-1998) of the journals Science, Nature, Proc Nat Acad Sci USA and Phys Rev B Condensed Matter.

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Abstract

Untersucht man die Verteilung der Autorenhäufigkeit in wissenschaftlichen Zeitschriften, hier kurz Journals Author Distri-bution (JAD) genannt indem man über mehrere Jahre die Verteilung der Häufigkeit prüft wie viele Autoren einmal, zweimal, dreimal etc. in dieser Zeitschrift erschienen, so zeigen sich charakteristische Verteilungen, die den allgemeinen Potenzgesetzen (power laws) folgen. Diese Verteilungen können als Typologie der speziellen Journale verwendet werden. Wie der Impact Factor, der Immediacy Factor oder die Halbwertzeit ist die JAD zur Kategorisierung einer Zeitschrift nützlich. Auffallend ist dabei, dass zwei Parameter, der Beginn der hyperbolischen Funktion und die Potenz in einem eher konstanten Verhältnis stehen. Den Konsequenzen dieser Beobachtung wird hier nachgegangen.

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Abstract

Recent Web-searching and -mining tools are combining text and link analysis to improve ranking and crawling algorithms. The central assumption behind such approaches is that there is a correiation between the graph structure of the Web and the text and meaning of pages. Here I formalize and empirically evaluate two general conjectures drawing connections from link information to lexical and semantic Web content. The link-content conjecture states that a page is similar to the pages that link to it, and the link-cluster conjecture that pages about the same topic are clustered together. These conjectures are offen simply assumed to hold, and Web search tools are built an such assumptions. The present quantitative confirmation sheds light an the connection between the success of the latest Web-mining techniques and the small world topology of the Web, with encouraging implications for the design of better crawling algorithms.

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Abstract

The Web is a huge source of information, and one of the main problems facing users is finding documents which correspond to their requirements. Apart from the problem of thematic relevance, the documents retrieved by search engines do not always meet the users' expectations. The document may be too general, or conversely too specialized, or of a different type from what the user is looking for, and so forth. We think that adding metadata to pages can considerably improve the process of searching for information an the Web. This article presents a possible typology for Web sites and pages, as weIl as a method for propagating metadata values, based an the study of the Web graph and more specifically the method of cocitation in this graph.