Characterization of the Impact of Sets of Scientific Papers: The Garfield (Impact) Factor

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Abstract

The Garfield (Impact) Factor (GF) is one of the most frequently used scientometric indicators. In the present article it is shown that the main factors determining the value of the mean GF representing a set of journals are the number of articles published recently (articles referencing) related to those published in a previous time period (articles to be referenced) and the mean number of references in journal papers referring to the time period selected. It has been proved further that GF corresponds to the mean chance for citedness of journal papers. A new indicator, Specific Impact Contribution (SIC), is introduced, which characterizes the contribution of a subset of articles or a journal to the total impact of the respective articles or journals. The SIC index relates the share of a journal in citations divided by that in publications within a set of papers or journals appropriately selected. It is shown, however, that the normalized GFs of journals and the normalized SIC indicators are identical measures within any set of journals selected. It may be stated therefore that Garfield Factors of journals (calculated correctly) are appropriate scientometric measures for characterizing the relative international eminence of journals within a set of journals appropriately selected. It is demonstrated further that SIC indicators (and so GF indexes) correspond to the (number of citations per paper) indicators generally used, within the same set of papers.

Original languageEnglish
Pages (from-to)431-435
Number of pages5
JournalJournal of the American Society for Information Science and Technology
Volume55
Issue number5
DOIs
Publication statusPublished - Mar 2004

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ASJC Scopus subject areas

  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Networks and Communications
  • Artificial Intelligence

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