Search (55 results, page 1 of 3)

  • × theme_ss:"Citation indexing"
  1. Hayer, L.: Lazarsfeld zitiert : eine bibliometrische Analyse (2008) 0.04 
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    Abstract
    Um sich einer Antwort auf die Frage anzunähern, welche Bedeutung der Nachlass eines Wissenschaftlers wie jener Paul F. Lazarsfelds (mit zahlreichen noch unveröffentlichten Schriften) für die aktuelle Forschung haben könne, kann untersucht werden, wie häufig dieser Wissenschaftler zitiert wird. Wenn ein Autor zitiert wird, wird er auch genutzt. Wird er über einen langen Zeitraum oft genutzt, ist vermutlich auch die Auseinandersetzung mit seinem Nachlass von Nutzen. Außerdem kann aufgrund der Zitierungen festgestellt werden, was aus dem Lebenswerk eines Wissenschaftlers für die aktuelle Forschung relevant erscheint. Daraus können die vordringlichen Fragestellungen in der Bearbeitung des Nachlasses abgeleitet werden. Die Aufgabe für die folgende Untersuchung lautete daher: Wie oft wird Paul F. Lazarsfeld zitiert? Dabei interessierte auch: Wer zitiert wo? Die Untersuchung wurde mit Hilfe der Meta-Datenbank "ISI Web of Knowledge" durchgeführt. In dieser wurde im "Web of Science" mit dem Werkzeug "Cited Reference Search" nach dem zitierten Autor (Cited Author) "Lazarsfeld P*" gesucht. Diese Suche ergab 1535 Referenzen (References). Werden alle Referenzen gewählt, führt dies zu 4839 Ergebnissen (Results). Dabei wurden die Datenbanken SCI-Expanded, SSCI und A&HCI verwendet. Bei dieser Suche wurden die Publikationsjahre 1941-2008 analysiert. Vor 1956 wurden allerdings nur sehr wenige Zitate gefunden: 1946 fünf, ansonsten maximal drei, 1942-1944 und 1949 überhaupt keines. Zudem ist das Jahr 2008 noch lange nicht zu Ende. (Es gab jedoch schon vor Ende März 24 Zitate!)
    Biographed
    Lazarsfeld, P.F.
    Date
    22. 6.2008 12:54:12
  2. Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003) 0.02 
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    Abstract
    Ahlgren, Jarneving, and. Rousseau review accepted procedures for author co-citation analysis first pointing out that since in the raw data matrix the row and column values are identical i,e, the co-citation count of two authors, there is no clear choice for diagonal values. They suggest the number of times an author has been co-cited with himself excluding self citation rather than the common treatment as zeros or as missing values. When the matrix is converted to a similarity matrix the normal procedure is to create a matrix of Pearson's r coefficients between data vectors. Ranking by r and by co-citation frequency and by intuition can easily yield three different orders. It would seem necessary that the adding of zeros to the matrix will not affect the value or the relative order of similarity measures but it is shown that this is not the case with Pearson's r. Using 913 bibliographic descriptions form the Web of Science of articles form JASIS and Scientometrics, authors names were extracted, edited and 12 information retrieval authors and 12 bibliometric authors each from the top 100 most cited were selected. Co-citation and r value (diagonal elements treated as missing) matrices were constructed, and then reconstructed in expanded form. Adding zeros can both change the r value and the ordering of the authors based upon that value. A chi-squared distance measure would not violate these requirements, nor would the cosine coefficient. It is also argued that co-citation data is ordinal data since there is no assurance of an absolute zero number of co-citations, and thus Pearson is not appropriate. The number of ties in co-citation data make the use of the Spearman rank order coefficient problematic.
    Date
    9. 7.2006 10:22:35
  3. Tay, A.: ¬The next generation discovery citation indexes : a review of the landscape in 2020 (2020) 0.02 
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    Abstract
    Conclusion There is a reason why Google Scholar and Web of Science/Scopus are kings of the hills in their various arenas. They have strong brand recogniton, a head start in development and a mass of eyeballs and users that leads to an almost virtious cycle of improvement. Competing against such well established competitors is not easy even when one has deep pockets (Microsoft) or a killer idea (scite). It will be interesting to see how the landscape will look like in 2030. Stay tuned for part II where I review each particular index.
    Date
    17.11.2020 12:22:59
  4. Safder, I.; Ali, M.; Aljohani, N.R.; Nawaz, R.; Hassan, S.-U.: Neural machine translation for in-text citation classification (2023) 0.01 
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  5. Vinkler, P.: ¬A quasi-quantitative citation model (1987) 0.01 
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  6. Moravcsik, M.J.; Murugesan, P.: Some results on the function and quality of citations (1975) 0.01 
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  7. Malanga, G.: Classifying and screening journal literature with citation data (1982) 0.01 
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    Source
    Universal classification I: subject analysis and ordering systems. Proc. of the 4th Int. Study Conf. on Classification Research, Augsburg, 28.6.-2.7.1982. Ed.: I. Dahlberg
  8. Rajan, T.N.; Guha, B.; Sayanarayana, R.: Associate relationship of concepts as seen through citations and citation index (1982) 0.01 
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    Source
    Universal classification II: subject analysis and ordering systems. Proc. of the 4th Int. Study Conf. on Classification research, Augsburg, 28.6.-2.7.1982. Ed.: I. Dahlberg
  9. ¬The Web of knowledge : Festschrift in honor of Eugene Garfield (2000) 0.01 
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    Editor
    Cronin, B. u. H.B. Atkins
    Footnote
    Rez. in: Knowledge organization 28(2001) no.1, S.45-46 (M.J. López Huertas u. E. Jiménez-Contreras); Password 2002, H.3, S.14-19 (W.G. Stock)
  10. Vinkler, P.: Relationships between the rate of scientific development and citations : the chance for citedness model (1996) 0.01 
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  11. Pichappan, P.: Levels of citation relation between papers (1996) 0.01 
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  12. Nacke, O.: Zitatenanalyse im engeren Sinne (1980) 0.01 
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    Source
    Deutscher Dokumentartag 1979, Willingen/Hochsauerland, 1.-5.10.1979. Das IuD-Programm heute - Online-Benutzergruppe - Bibliometrie, Scientometrie - Terminologiearbeit - Datenschutz - Tariffragen, Berufsbilder - Informationsmarkt - Gesprächskreise. Bearb.: M. von der Laake u. H. Strohl-Goebel
  13. Nacke, O.: Fehlerquellen bei der Zitatenanalyse (1980) 0.01 
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    Source
    Deutscher Dokumentartag 1979, Willingen/Hochsauerland, 1.-5.10.1979. Das IuD-Programm heute - Online-Benutzergruppe - Bibliometrie, Scientometrie - Terminologiearbeit - Datenschutz - Tariffragen, Berufsbilder - Informationsmarkt - Gesprächskreise. Bearb.: M. von der Laake u. H. Strohl-Goebel
  14. 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.
  15. Belter, C.W.: Citation analysis as a literature search method for systematic reviews (2016) 0.01 
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    Abstract
    Systematic reviews are essential for evaluating biomedical treatment options, but the growing size and complexity of the available biomedical literature combined with the rigor of the systematic review method mean that systematic reviews are extremely difficult and labor-intensive to perform. In this article, I propose a method of searching the literature by systematically mining the various types of citation relationships between articles. I then test the method by comparing its precision and recall to that of 14 published systematic reviews. The method successfully retrieved 74% of the studies included in these reviews and 90% of the studies it could reasonably be expected to retrieve. The method also retrieved fewer than half of the total number of publications retrieved by these reviews and can be performed in substantially less time. This suggests that the proposed method offers a promising complement to traditional text-based methods of literature identification and retrieval for systematic reviews.
  16. Osareh, F.: Bibliometrics, citation analysis and co-citation analysis : a review of literature I (1996) 0.01 
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  17. Haridasan, S.; Kulshrestha, V.K.: Citation analysis of scholarly communication in the journal Knowledge Organization (2007) 0.01 
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    Content
    Vgl..: Burton, P.F.: On reading "The banning of books in libraries". In: Library review. 56(2007) no.3, S.197-199.
  18. Daquino, M.; Peroni, S.; Shotton, D.; Colavizza, G.; Ghavimi, B.; Lauscher, A.; Mayr, P.; Romanello, M.; Zumstein, P.: ¬The OpenCitations Data Model (2020) 0.01 
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  19. Fröhlich, G.: ¬Das Messen des leicht Meßbaren : Output-Indikatoren, Impact-Maße: Artefakte der Szeintometrie? (1999) 0.01 
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    Footnote
    Zuerst publiziert in: Kommunikation statt Markt: Zu einer alternativen Theorie der Informationsgesellschaft. Hrsg.: J. Becker u. W. Göhring. Sankt Augustin: GMD. (GMD Report; 61) S.27-38.
  20. Alvarez, P.; Pulgarin, A.: ¬The Rasch model : measuring the impact of scientific journals: analytical chemistry (1996) 0.01 
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