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Do new research issues attract more citations? A comparison between 25 Scopus subject categories

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  • Mike Thelwall
  • Pardeep Sud

Abstract

Finding new ways to help researchers and administrators understand academic fields is an important task for information scientists. Given the importance of interdisciplinary research, it is essential to be aware of disciplinary differences in aspects of scholarship, such as the significance of recent changes in a field. This paper identifies potential changes in 25 subject categories through a term comparison of words in article titles, keywords and abstracts in 1 year compared to the previous 4 years. The scholarly influence of new research issues is indirectly assessed with a citation analysis of articles matching each trending term. While topic‐related words dominate the top terms, style, national focus, and language changes are also evident. Thus, as reflected in Scopus, fields evolve along multiple dimensions. Moreover, while articles exploiting new issues are usually more cited in some fields, such as Organic Chemistry, they are usually less cited in others, including History. The possible causes of new issues being less cited include externally driven temporary factors, such as disease outbreaks, and internally driven temporary decisions, such as a deliberate emphasis on a single topic (e.g., through a journal special issue).

Suggested Citation

  • Mike Thelwall & Pardeep Sud, 2021. "Do new research issues attract more citations? A comparison between 25 Scopus subject categories," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(3), pages 269-279, March.
  • Handle: RePEc:bla:jinfst:v:72:y:2021:i:3:p:269-279
    DOI: 10.1002/asi.24401
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    References listed on IDEAS

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    Cited by:

    1. Siudem, Grzegorz & Nowak, Przemysław & Gagolewski, Marek, 2022. "Power laws, the Price model, and the Pareto type-2 distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    2. Tuba Bircan & Almila Alkim Akdag Salah, 2022. "A Bibliometric Analysis of the Use of Artificial Intelligence Technologies for Social Sciences," Mathematics, MDPI, vol. 10(23), pages 1-17, November.
    3. Peter Sjögårde & Fereshteh Didegah, 2022. "The association between topic growth and citation impact of research publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1903-1921, April.

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