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Journal impact and proximity: An assessment using bibliographic features

Author

Listed:
  • Chaoqun Ni
  • Debora Shaw
  • Sean M. Lind
  • Ying Ding

Abstract

Journals in the Information Science & Library Science category of Journal Citation Reports (JCR) were compared using both bibliometric and bibliographic features. Data collected covered journal impact factor (JIF), number of issues per year, number of authors per article, longevity, editorial board membership, frequency of publication, number of databases indexing the journal, number of aggregators providing full‐text access, country of publication, JCR categories, Dewey decimal classification, and journal statement of scope. Three features significantly correlated with JIF: number of editorial board members and number of JCR categories in which a journal is listed correlated positively; journal longevity correlated negatively with JIF. Coword analysis of journal descriptions provided a proximity clustering of journals, which differed considerably from the clusters based on editorial board membership. Finally, a multiple linear regression model was built to predict the JIF based on all the collected bibliographic features.

Suggested Citation

  • Chaoqun Ni & Debora Shaw & Sean M. Lind & Ying Ding, 2013. "Journal impact and proximity: An assessment using bibliographic features," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(4), pages 802-817, April.
    • Handle: RePEc:bla:jamist:v:64:y:2013:i:4:p:802-817
    DOI: 10.1002/asi.22778
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    Cited by:

    1. Alexandre Rodrigues Oliveira & Carlos Fernando Mello, 2016. "Importance and susceptibility of scientific productivity indicators: two sides of the same coin," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 697-722, November.
    2. Sugimoto, Cassidy R. & Larivière, Vincent & Ni, Chaoqun & Cronin, Blaise, 2013. "Journal acceptance rates: A cross-disciplinary analysis of variability and relationships with journal measures," Journal of Informetrics, Elsevier, vol. 7(4), pages 897-906.
    3. Croft, William L. & Sack, Jörg-Rüdiger, 2022. "Predicting the citation count and CiteScore of journals one year in advance," Journal of Informetrics, Elsevier, vol. 16(4).

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