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  • × theme_ss:"Informetrie"
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  1. Park, H.; You, S.; Wolfram, D.: Informal data citation for data sharing and reuse is more common than formal data citation in biomedical fields (2018) 0.00
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  2. Zhou, H.; Guns, R.; Engels, T.C.E.: Are social sciences becoming more interdisciplinary? : evidence from publications 1960-2014 (2022) 0.00
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  3. Cui, Y.; Wang, Y.; Liu, X.; Wang, X.; Zhang, X.: Multidimensional scholarly citations : characterizing and understanding scholars' citation behaviors (2023) 0.00
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    Abstract
    This study investigates scholars' citation behaviors from a fine-grained perspective. Specifically, each scholarly citation is considered multidimensional rather than logically unidimensional (i.e., present or absent). Thirty million articles from PubMed were accessed for use in empirical research, in which a total of 15 interpretable features of scholarly citations were constructed and grouped into three main categories. Each category corresponds to one aspect of the reasons and motivations behind scholars' citation decision-making during academic writing. Using about 500,000 pairs of actual and randomly generated scholarly citations, a series of Random Forest-based classification experiments were conducted to quantitatively evaluate the correlation between each constructed citation feature and citation decisions made by scholars. Our experimental results indicate that citation proximity is the category most relevant to scholars' citation decision-making, followed by citation authority and citation inertia. However, big-name scholars whose h-indexes rank among the top 1% exhibit a unique pattern of citation behaviors-their citation decision-making correlates most closely with citation inertia, with the correlation nearly three times as strong as that of their ordinary counterparts. Hopefully, the empirical findings presented in this paper can bring us closer to characterizing and understanding the complex process of generating scholarly citations in academia.
  4. Jiao, H.; Qiu, Y.; Ma, X.; Yang, B.: Dissmination effect of data papers on scientific datasets (2024) 0.00
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  5. Czepel, R.: ¬Die Geographie der wissenschaftlichen Zitierung (2003) 0.00
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    Source
    Online Mitteilungen. 2003, Nr.77, S.34-36 [=Mitteilungen VÖB 56(2003) H.3/4]
  6. Bibliometrische Analysen - ein Beitrag für ein gerechtes Notensystem in der Forschung? : Konferenz in Jülich (2004) 0.00
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    Source
    BuB. 56(2004) H.2, S.101
  7. Glänzel, W.; Debackere, K.: Messen von Wissenschaftlicher Kommunikation und Forschungsleistung : Möglichkeiten und Beschränkungen bibliometrischer Methoden (2005) 0.00
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    Source
    Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare. 58(2005) H.2, S.9-20
  8. Petersen, A.; Münch, V.: STN® AnaVist(TM) holt verborgenes Wissen aus Recherche-Ergebnissen : Neue Software analysiert und visualisiert Marktaufteilung, Forschung und Patentaktivitäten (2005) 0.00
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    Source
    Information - Wissenschaft und Praxis. 56(2005) H.5/6, S.319-322
  9. Stock, W.G.; Weber, S.: Facets of informetrics : Preface (2006) 0.00
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    Source
    Information - Wissenschaft und Praxis. 57(2006) H.8, S.385-389
  10. Neuhaus, C.; Marx, W.; Daniel, H.-W.: ¬The publication and citation impact profiles of Angewandte Chemie and the Journal of the American Chemical Society based on the sections of Chemical Abstracts : a case study on the limitations of the Journal Impact Factor (2009) 0.00
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