• Title of article

    Classification of individual articles from all of science by research level

  • Author/Authors

    Boyack، نويسنده , , Kevin W. and Patek، نويسنده , , Michael and Ungar، نويسنده , , Lyle H. and Yoon، نويسنده , , Patrick and Klavans، نويسنده , , Richard، نويسنده ,

  • Issue Information
    فصلنامه با شماره پیاپی سال 2014
  • Pages
    12
  • From page
    1
  • To page
    12
  • Abstract
    A system of four research levels, designed to classify scientific journals from most applied to most basic, was introduced by Francis Narin and colleagues in the 1970s. Research levels have been used since that time to characterize research at institutional and departmental levels. Currently, less than half of all articles published are in journals that been classified by research level. There is thus a need for the notion of research level to be extended in a way that all articles can be so classified. This article reports on a new model – trained from title and abstract words and cited references – that classifies individual articles by research level. The model covers all of science, and has been used to classify over 25 million articles from Scopus by research level. The final model and set of classified articles are further characterized.
  • Keywords
    Research level , Basic Science , Multinomial logistic regression model , Article-level classification , applied science
  • Journal title
    Journal of Informetrics
  • Serial Year
    2014
  • Journal title
    Journal of Informetrics
  • Record number

    1387601