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Quantifying the interdisciplinarity of scientific journals and fields

Author

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  • Silva, F.N.
  • Rodrigues, F.A.
  • Oliveira, O.N.
  • da F. Costa, L.

Abstract

There is an overall perception of increased interdisciplinarity in science, but this is difficult to confirm quantitatively owing to the lack of adequate methods to evaluate subjective phenomena. This is no different from the difficulties in establishing quantitative relationships in human and social sciences. In this paper we quantified the interdisciplinarity of scientific journals and science fields by using an entropy measurement based on the diversity of the subject categories of journals citing a specific journal. The methodology consisted in building citation networks using the Journal Citation Reports® database, in which the nodes were journals and edges were established based on citations among journals. The overall network for the 11-year period (1999–2009) studied was small-world and followed a power-law with exponential cutoff distribution with regard to the in-strength. Upon visualizing the network topology an overall structure of the various science fields could be inferred, especially their interconnections. We confirmed quantitatively that science fields are becoming increasingly interdisciplinary, with the degree of interdisplinarity (i.e. entropy) correlating strongly with the in-strength of journals and with the impact factor.

Suggested Citation

  • Silva, F.N. & Rodrigues, F.A. & Oliveira, O.N. & da F. Costa, L., 2013. "Quantifying the interdisciplinarity of scientific journals and fields," Journal of Informetrics, Elsevier, vol. 7(2), pages 469-477.
    • Handle: RePEc:eee:infome:v:7:y:2013:i:2:p:469-477
    DOI: 10.1016/j.joi.2013.01.007
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    Cited by:

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    2. Jingjing Ren & Fang Wang & Minglu Li, 2023. "Dynamics and characteristics of interdisciplinary research in scientific breakthroughs: case studies of Nobel-winning research in the past 120 years," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4383-4419, August.
    3. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2019. "On the interplay between normalisation, bias, and performance of paper impact metrics," Journal of Informetrics, Elsevier, vol. 13(1), pages 270-290.
    4. Brito, Ana C.M. & Silva, Filipi N. & Amancio, Diego R., 2021. "Associations between author-level metrics in subsequent time periods," Journal of Informetrics, Elsevier, vol. 15(4).
    5. Alfonso Ávila-Robinson & Cristian Mejia & Shintaro Sengoku, 2021. "Are bibliometric measures consistent with scientists’ perceptions? The case of interdisciplinarity in research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7477-7502, September.
    6. Stepanić Josip & Zoroja Jovana & Šimičević Vanja, 2017. "Case Study in Interdisciplinary Scientific Communication: A Decade of the INDECS Journal," Business Systems Research, Sciendo, vol. 8(2), pages 101-114, September.
    7. Shuto Miyashita & Shintaro Sengoku, 2021. "Scientometrics for management of science: collaboration and knowledge structures and complexities in an interdisciplinary research project," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7419-7444, September.
    8. Maribel Blasco, 2022. "“We’re Just Geeks”: Disciplinary Identifications Among Business Students and Their Implications for Personal Responsibility," Journal of Business Ethics, Springer, vol. 178(1), pages 279-302, June.
    9. Hric, Darko & Kaski, Kimmo & Kivelä, Mikko, 2018. "Stochastic block model reveals maps of citation patterns and their evolution in time," Journal of Informetrics, Elsevier, vol. 12(3), pages 757-783.
    10. Chiara Carusi & Giuseppe Bianchi, 2020. "A look at interdisciplinarity using bipartite scholar/journal networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 867-894, February.
    11. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2019. "Globalised vs averaged: Bias and ranking performance on the author level," Journal of Informetrics, Elsevier, vol. 13(1), pages 299-313.
    12. Silva, Filipi N. & Amancio, Diego R. & Bardosova, Maria & Costa, Luciano da F. & Oliveira, Osvaldo N., 2016. "Using network science and text analytics to produce surveys in a scientific topic," Journal of Informetrics, Elsevier, vol. 10(2), pages 487-502.
    13. Mingers, John & Leydesdorff, Loet, 2015. "A review of theory and practice in scientometrics," European Journal of Operational Research, Elsevier, vol. 246(1), pages 1-19.
    14. Antonio Protic & Biserka Runje & Josip Stepanic, 2013. "Distribution of Citations in one Volume of a Journal," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 11(2), pages 227-237.
    15. Juan María Hernández & Pablo Dorta-González, 2020. "Interdisciplinarity Metric Based on the Co-Citation Network," Mathematics, MDPI, vol. 8(4), pages 1-8, April.
    16. Qing Ke, 2023. "Interdisciplinary research and technological impact: evidence from biomedicine," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2035-2077, April.
    17. Wang L. & Coccia M., 2015. "Evolutionary convergence of the patterns of international research collaborations across scientific fields," MERIT Working Papers 2015-011, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

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