Search (225 results, page 3 of 12)

  • × theme_ss:"Informetrie"
  • × type_ss:"a"
  1. Cronin, B.; Meho, L.I.: Using the h-index to rank influential information scientists (2006) 0.01
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  2. Cronin, B.; Meho, L.I.: Applying the author affiliation index to library and information science journals (2008) 0.01
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  3. Zhang, L.; Thijs, B.; Glänzel, W.: What does scientometrics share with other "metrics" sciences? (2013) 0.01
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  4. Herb, U.; Geith, U.: Kriterien der qualitativen Bewertung wissenschaftlicher Publikationen : Befunde aus dem Projekt visOA (2020) 0.01
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    Abstract
    Dieser Beitrag beschreibt a) die Ergebnisse einer Literaturstudie zur qualitativen Wahrnehmung wissenschaftlicher Publikationen, b) die Konstruktion eines daraus abgeleiteten Kriterienkatalogs zur Wahrnehmung der Qualität wissenschaftlicher Publikationen sowie c) der Überprüfung dieses Katalogs in qualitativen Interviews mit Wissenschaflterinnen und Wissenschaftlern aus dem Fachspektrum Chemie, Physik, Biologie, Materialwissenschaft und Engineering. Es zeigte sich, dass die Wahrnehmung von Qualität auf äußerlichen und von außen herangetragenen Faktoren, inhaltlichen / semantischen Faktoren und sprachlichen, syntaktischen sowie strukturellen Faktoren beruht.
  5. Li, T.-C.: Reference sources in periodicals : research note (1995) 0.01
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    Abstract
    Presents a list of 53 periodicals in 22 subject fields which regularly provide bibliographies of theses, research in progress and patents in their particular subject field. The fields of business, economics, history and literature have most periodical listings of dissertations and theses. Also lists 63 periodicals in 25 sub-disciplines which provide rankings or ratings. Rankings and ratings information predominates in the fields of business, sports and games, finance and banking, and library and information science
  6. Pichappan, P.; Sangaranachiyar, S.: Ageing approach to scientific eponyms (1996) 0.01
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    Footnote
    Report presented at the 16th National Indian Association of Special Libraries and Information Centres Seminar Special Interest Group Meeting on Informatrics in Bombay, 19-22 Dec 94
  7. Mommoh, O.M.: Subject analysis of post-graduate theses in library, archival and information science at Ahmadu Bello University, Zaria (1995/96) 0.01
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    Source
    Library focus. 13/14(1995/96), S.22-25
  8. Chongde, W.; Zhe, W.: Evaluation of the models for Bradford's law (1998) 0.01
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    Date
    22. 5.1999 19:12:28
  9. Tijssen, R.J.W.; Wijk, E. van: ¬The global science base of information and communication technologies : bibliometric analysis of ICT research papers (1998) 0.01
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    Date
    22. 5.1999 19:26:54
  10. Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006) 0.01
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    Date
    4.12.2006 12:12:22
  11. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.01
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    Date
    22. 8.2014 17:05:18
  12. Ohly, P.: Dimensions of globality : a bibliometric analysis (2016) 0.01
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    Date
    20. 1.2019 11:22:31
  13. Pudovkin, A.I.; Garfield, E.: Algorithmic procedure for finding semantically related journals (2002) 0.01
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    Abstract
    Journal Citation Reports provides a classification of journals most heavily cited by a given journal and which most heavily cite that journal, but size variation is not taken into account. Pudovkin and Garfield suggest a procedure for meeting this difficulty. The relatedness of journal i to journal j is determined by the number of citations from journal i to journal j in a given year normalized by the product of the papers published in the j journal in that year times the number of references cited in the i journal in that year. A multiplier of ten to the sixth is suggested to bring the values into an easily perceptible range. While citations received depend upon the overall cumulative number of papers published by a journal, the current year is utilized since that data is available in JCR. Citations to current year papers would be quite low in most fields and thus not included. To produce the final index, the maximum of the A citing B value, and the B citing A value is chosen and used to indicate the closeness of the journals. The procedure is illustrated for the journal Genetics.
  14. Zhao, D.; Strotmann, A.: Can citation analysis of Web publications better detect research fronts? (2007) 0.01
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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.
  15. Milojevic, S.; Sugimoto, C.R.; Yan, E.; Ding, Y.: ¬The cognitive structure of Library and Information Science : analysis of article title words (2011) 0.01
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    Abstract
    This study comprises a suite of analyses of words in article titles in order to reveal the cognitive structure of Library and Information Science (LIS). The use of title words to elucidate the cognitive structure of LIS has been relatively neglected. The present study addresses this gap by performing (a) co-word analysis and hierarchical clustering, (b) multidimensional scaling, and (c) determination of trends in usage of terms. The study is based on 10,344 articles published between 1988 and 2007 in 16 LIS journals. Methodologically, novel aspects of this study are: (a) its large scale, (b) removal of non-specific title words based on the "word concentration" measure (c) identification of the most frequent terms that include both single words and phrases, and (d) presentation of the relative frequencies of terms using "heatmaps". Conceptually, our analysis reveals that LIS consists of three main branches: the traditionally recognized library-related and information-related branches, plus an equally distinct bibliometrics/scientometrics branch. The three branches focus on: libraries, information, and science, respectively. In addition, our study identifies substructures within each branch. We also tentatively identify "information seeking behavior" as a branch that is establishing itself separate from the three main branches. Furthermore, we find that cognitive concepts in LIS evolve continuously, with no stasis since 1992. The most rapid development occurred between 1998 and 2001, influenced by the increased focus on the Internet. The change in the cognitive landscape is found to be driven by the emergence of new information technologies, and the retirement of old ones.
  16. Xu, C.; Ma, B.; Chen, X.; Ma, F.: Social tagging in the scholarly world (2013) 0.01
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    Abstract
    The number of research studies on social tagging has increased rapidly in the past years, but few of them highlight the characteristics and research trends in social tagging. A set of 862 academic documents relating to social tagging and published from 2005 to 2011 was thus examined using bibliometric analysis as well as the social network analysis technique. The results show that social tagging, as a research area, develops rapidly and attracts an increasing number of new entrants. There are no key authors, publication sources, or research groups that dominate the research domain of social tagging. Research on social tagging appears to focus mainly on the following three aspects: (a) components and functions of social tagging (e.g., tags, tagging objects, and tagging network), (b) taggers' behaviors and interface design, and (c) tags' organization and usage in social tagging. The trend suggest that more researchers turn to the latter two integrated with human computer interface and information retrieval, although the first aspect is the fundamental one in social tagging. Also, more studies relating to social tagging pay attention to multimedia tagging objects and not only text tagging. Previous research on social tagging was limited to a few subject domains such as information science and computer science. As an interdisciplinary research area, social tagging is anticipated to attract more researchers from different disciplines. More practical applications, especially in high-tech companies, is an encouraging research trend in social tagging.
  17. Ye, F.Y.; Bornmann, L.: "Smart girls" versus "sleeping beauties" in the sciences : the identification of instant and delayed recognition by using the citation angle (2018) 0.01
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    Abstract
    In recent years, a number of studies have introduced methods for identifying papers with delayed recognition (so called "sleeping beauties," SBs) or have presented single publications as cases of SBs. Most recently, Ke, Ferrara, Radicchi, and Flammini (2015, Proceedings of the National Academy of Sciences of the USA, 112(24), 7426-7431) proposed the so called "beauty coefficient" (denoted as B) to quantify how much a given paper can be considered as a paper with delayed recognition. In this study, the new term smart girl (SG) is suggested to differentiate instant credit or "flashes in the pan" from SBs. Although SG and SB are qualitatively defined, the dynamic citation angle ß is introduced in this study as a simple way for identifying SGs and SBs quantitatively - complementing the beauty coefficient B. The citation angles for all articles from 1980 (n?=?166,870) in natural sciences are calculated for identifying SGs and SBs and their extent. We reveal that about 3% of the articles are typical SGs and about 0.1% typical SBs. The potential advantages of the citation angle approach are explained.
  18. Bornmann, L.; Mutz, R.: Growth rates of modern science : a bibliometric analysis based on the number of publications and cited references (2015) 0.01
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    Abstract
    Many studies (in information science) have looked at the growth of science. In this study, we reexamine the question of the growth of science. To do this we (a) use current data up to publication year 2012 and (b) analyze the data across all disciplines and also separately for the natural sciences and for the medical and health sciences. Furthermore, the data were analyzed with an advanced statistical technique-segmented regression analysis-which can identify specific segments with similar growth rates in the history of science. The study is based on two different sets of bibliometric data: (a) the number of publications held as source items in the Web of Science (WoS, Thomson Reuters) per publication year and (b) the number of cited references in the publications of the source items per cited reference year. We looked at the rate at which science has grown since the mid-1600s. In our analysis of cited references we identified three essential growth phases in the development of science, which each led to growth rates tripling in comparison with the previous phase: from less than 1% up to the middle of the 18th century, to 2 to 3% up to the period between the two world wars, and 8 to 9% to 2010.
  19. Cronin, B.; Weaver-Wozniak, S.: Online access to acknowledgements (1993) 0.01
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  20. Debackere, K.; Clarysse, B.: Advanced bibliometric methods to model the relationship between entry behavior and networking in emerging technological communities (1998) 0.01
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