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  • × theme_ss:"Informetrie"
  • × language_ss:"d"
  1. Herb, U.; Beucke, D.: ¬Die Zukunft der Impact-Messung : Social Media, Nutzung und Zitate im World Wide Web (2013) 0.12
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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.
  2. Stock, W.G.: Informetrische Untersuchungsmethoden auf der Grundlage der Textwortmethode (1984) 0.04
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    Abstract
    Discusses the mathematical basis of scientometrics involving text keywords independent of thesauri and classification schemes
    Source
    International classification. 11(1984) no.3, S.151-157
  3. Stock, W.G.: ¬Die Wichtigkeit wissenschaftlicher Dokumente relativ zu gegebenen Thematiken (1981) 0.00
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    Abstract
    Scientific documents are more or less important in relation to give subjects and this importance can be measured. An empirical investigation into philosophical information was carried out using a weighting algorithm developed by N. Henrichs which results in a distribution by weighting of documents on an average philosophical subject. With the aid of statistical methods a threshold value can be obtained that separates the important and unimportant documents on a subject. The knowledge of theis threshold value is important for various practical and theoretic questions: providing new possibilities for research strategy in information retrieval; evaluation of the 'titleworthiness' of subjects by comparison of document titles and themes for which the document at hand is important; and making available data on thematic trends for scientific results
  4. Positionspapier der DMV zur Verwendung bibliometrischer Daten (2020) 0.00
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    Abstract
    Bibliometrische Daten werden heute zunehmend in der Evaluation von Forschungsergebnissen benutzt. Diese Anwendungen reichen von der (indirekten) Verwendung bei der Peer-Evaluation von Drittmittelanträgen über die Beurteilung von Bewerbungen in Berufungskommissionen oder Anträgen für Forschungszulagen bis hin zur systematischen Erhebung von forschungsorientierten Kennzahlen von Institutionen. Mit diesem Dokument will die DMV ihren Mitgliedern eine Diskussionsgrundlage zur Verwendung bibliometrischer Daten im Zusammenhang mit der Evaluation von Personen und Institutionen im Fachgebiet Mathematik zur Verfügung stellen, insbesondere auch im Vergleich zu anderen Fächern. Am Ende des Texts befindet sich ein Glossar, in dem die wichtigsten Begriffe kurz erläutert werden.
  5. Tüür-Fröhlich, T.: Blackbox SSCI : Datenerfassung und Datenverarbeitung bei der kommerziellen Indexierung von Zitaten (2019) 0.00
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    Abstract
    Zahlreiche Autoren, Autorinnen und kritische Initiativen (z. B. DORA) kritisieren den zu hohen und schädlichen Einfluss quantitativer Daten, welche akademische Instanzen für Evaluationszwecke heranziehen. Wegen des großen Einflusses der globalen Zitatdatenbanken von Thomson Reuters (bzw. Clarivate Analytics) auf die Bewertung der wissenschaftlichen Leistungen von Forscherinnen und Forschern habe ich extensive qualitative und quantitative Fallstudien zur Datenqualität des Social Sciences Citation Index (SSCI) durchgeführt, d. h. die Originaleinträge mit den SSCI-Datensätzen verglichen. Diese Fallstudien zeigten schwerste - nie in der Literatur erwähnte - Fehler, Verstümmelungen, Phantomautoren, Phantomwerke (Fehlerrate in der Fallstudie zu Beebe 2010, Harvard Law Review: 99 Prozent). Über die verwendeten Datenerfassungs- und Indexierungsverfahren von TR bzw. Clarivate Analytics ist nur wenig bekannt. Ein Ergebnis meiner Untersuchungen: Bei der Indexierung von Verweisen in Fußnoten (wie in den Rechtswissenschaften, gerade auch der USA, vorgeschrieben) scheinen die verwendeten Textanalyse-Anwendungen und -Algorithmen völlig überfordert. Eine Qualitätskontrolle scheint nicht stattzufinden. Damit steht der Anspruch des SSCI als einer multidisziplinären Datenbank zur Debatte. Korrekte Zitate in den Fußnoten des Originals können zu Phantom-Autoren, Phantom-Werken und Phantom-Referenzen degenerieren. Das bedeutet: Sämtliche Zeitschriften und Disziplinen, deren Zeitschriften und Büchern dieses oder ähnliche Zitierverfahren verwenden (Oxford-Style), laufen Gefahr, aufgrund starker Zitatverluste falsch, d. h. unterbewertet, zu werden. Wie viele UBOs (Unidentifiable Bibliographic Objects) sich in den Datenbanken SCI, SSCI und AHCI befinden, wäre nur mit sehr aufwändigen Prozeduren zu klären. Unabhängig davon handelt es sich, wie bei fast allen in meinen Untersuchungen gefundenen fatalen Fehlern, eindeutig um endogene Fehler in den Datenbanken, die nicht, wie oft behauptet, angeblich falsch zitierenden Autorinnen und Autoren zugeschrieben werden können, sondern erst im Laufe der Dateneingabe und -verarbeitung entstehen.
  6. Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006) 0.00
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    Date
    4.12.2006 12:12:22
  7. Schlögl, C.: Internationale Sichtbarkeit der europäischen und insbesondere der deutschsprachigen Informationswissenschaft (2013) 0.00
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    Date
    22. 3.2013 14:04:09
  8. H-Index auch im Web of Science (2008) 0.00
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    Date
    6. 4.2008 19:04:22
  9. Jovanovic, M.: ¬Eine kleine Frühgeschichte der Bibliometrie (2012) 0.00
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    Date
    22. 7.2012 19:23:32
  10. ¬Die deutsche Zeitschrift für Dokumentation, Informationswissenschaft und Informationspraxis von 1950 bis 2011 : eine vorläufige Bilanz in vier Abschnitten (2012) 0.00
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    Date
    22. 7.2012 19:35:26
  11. Ball, R.: Wissenschaftsindikatoren im Zeitalter digitaler Wissenschaft (2007) 0.00
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    Date
    23.12.2007 19:22:21
  12. Hayer, L.: Lazarsfeld zitiert : eine bibliometrische Analyse (2008) 0.00
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    Date
    22. 6.2008 12:54:12
  13. Wettlauf der Wissenschaft (2004) 0.00
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    Source
    Online Mitteilungen. 2004, Nr.79, S.22-23 [=Mitteilungen VÖB 57(2004) H.2]