IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v57y2023i3d10.1007_s11135-022-01467-w.html
   My bibliography  Save this article

Scientific journal disciplinarity quantification and sorting using a network index

Author

Listed:
  • Inácio Sousa Fadigas

    (State University of Feira de Santana)

  • Marcos Grilo

    (State University of Feira de Santana)

  • Hernane Borges Barros Pereira

    (SENAI Cimatec University Center
    State University of Bahia)

Abstract

In this article, we present the results of research using a network index, called the vertex reduction factor, to quantify and to sort the disciplinarity of journals. The index is based on the repeatability of article title words. Titles were obtained from 16 journals from different areas of knowledge. We took as a reference the Scopus database, which classifies the journals into 4 main areas, divided into 26 thematic areas. We define a Journal’s Disciplinarity Factor, independent of the size of the network, from which it is possible to quantify and rank the journals according to their greater or lesser multidisciplinary nature. We found that journals such as Science and Nature, self-declared as multidisciplinary, presented less multidisciplinary potential than expected, compared with other journals.

Suggested Citation

  • Inácio Sousa Fadigas & Marcos Grilo & Hernane Borges Barros Pereira, 2023. "Scientific journal disciplinarity quantification and sorting using a network index," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2563-2573, June.
    • Handle: RePEc:spr:qualqt:v:57:y:2023:i:3:d:10.1007_s11135-022-01467-w
    DOI: 10.1007/s11135-022-01467-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-022-01467-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11135-022-01467-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fadigas, I.S. & Pereira, H.B.B., 2013. "A network approach based on cliques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2576-2587.
    2. Grilo, M. & Fadigas, I.S. & Miranda, J.G.V. & Cunha, M.V. & Monteiro, R.L.S. & Pereira, H.B.B., 2017. "Robustness in semantic networks based on cliques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 94-102.
    3. Pereira, H.B.B. & Fadigas, I.S. & Monteiro, R.L.S. & Cordeiro, A.J.A. & Moret, M.A., 2016. "Density: A measure of the diversity of concepts addressed in semantic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 81-84.
    4. Pereira, H.B.B. & Fadigas, I.S. & Senna, V. & Moret, M.A., 2011. "Semantic networks based on titles of scientific papers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1192-1197.
    5. Loet Leydesdorff, 2007. "Betweenness centrality as an indicator of the interdisciplinarity of scientific journals," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(9), pages 1303-1319, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lin Zhang & Ronald Rousseau & Wolfgang Glänzel, 2016. "Diversity of references as an indicator of the interdisciplinarity of journals: Taking similarity between subject fields into account," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1257-1265, May.
    2. Su, Hsin-Ning & Moaniba, Igam M., 2017. "Investigating the dynamics of interdisciplinary evolution in technology developments," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 12-23.
    3. Frid-Nielsen, Snorre Sylvester & Rubin, Olivier & Baekkeskov, Erik, 2019. "The state of social science research on antimicrobial resistance," Social Science & Medicine, Elsevier, vol. 242(C).
    4. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    5. Rafols, Ismael & Leydesdorff, Loet & O’Hare, Alice & Nightingale, Paul & Stirling, Andy, 2012. "How journal rankings can suppress interdisciplinary research: A comparison between Innovation Studies and Business & Management," Research Policy, Elsevier, vol. 41(7), pages 1262-1282.
    6. Gong, Jue & Wang, Gang-Jin & Zhou, Yang & Zhu, You & Xie, Chi & Foglia, Matteo, 2023. "Spreading of cross-market volatility information: Evidence from multiplex network analysis of volatility spillovers," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    7. Ran Xu & Navid Ghaffarzadegan, 2018. "Neuroscience bridging scientific disciplines in health: Who builds the bridge, who pays for it?," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 1183-1204, November.
    8. Raymundo das Neves Machado & Benjamín Vargas-Quesada & Jacqueline Leta, 2016. "Intellectual structure in stem cell research: exploring Brazilian scientific articles from 2001 to 2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 525-537, February.
    9. Lina Xu & Steven Dellaportas & Zhiqiang Yang & Jin Wang, 2023. "More on the relationship between interdisciplinary accounting research and citation impact," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 4779-4803, December.
    10. Bilong Shen & Weimin Zheng & Kathleen M. Carley, 2018. "Urban Activity Mining Framework for Ride Sharing Systems Based on Vehicular Social Networks," Networks and Spatial Economics, Springer, vol. 18(3), pages 705-734, September.
    11. Wei Wang & Dechao Ma & Fengzhi Wu & Mengxin Sun & Shuangqing Xu & Qiuyue Hua & Ziyuan Sun, 2023. "Exploring the Knowledge Structure and Hotspot Evolution of Greenwashing: A Visual Analysis Based on Bibliometrics," Sustainability, MDPI, vol. 15(3), pages 1-35, January.
    12. Etienne Farvaque & Frédéric Gannon, 2018. "Profiling giants: the networks and influence of Buchanan and Tullock," Public Choice, Springer, vol. 175(3), pages 277-302, June.
    13. An‐Pang Wang & Che‐Wei Chang & Juin‐Ming Tsai & Shiu‐Wan Hung, 2021. "A performance evaluation of Major League Baseball teams: An integrated social network and data envelopment analysis," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(6), pages 1421-1434, September.
    14. Mark Kibanov & Raphael H. Heiberger & Simone Rödder & Martin Atzmueller & Gerd Stumme, 2019. "Social studies of scholarly life with sensor-based ethnographic observations," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1387-1428, June.
    15. Nesari, Mohammad & Naghizadeh, Mohammad & Ghazinoori, Soroush & Manteghi, Manoochehr, 2022. "The evolution of socio-technical transition studies: A scientometric analysis," Technology in Society, Elsevier, vol. 68(C).
    16. Shiji Chen & Yanhui Song & Fei Shu & Vincent Larivière, 2022. "Interdisciplinarity and impact: the effects of the citation time window," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2621-2642, May.
    17. Carusi, Chiara & Bianchi, Giuseppe, 2019. "Scientific community detection via bipartite scholar/journal graph co-clustering," Journal of Informetrics, Elsevier, vol. 13(1), pages 354-386.
    18. Yan, Weiwei & Zhang, Yin, 2018. "Research universities on the ResearchGate social networking site: An examination of institutional differences, research activity level, and social networks formed," Journal of Informetrics, Elsevier, vol. 12(1), pages 385-400.
    19. Zhang, Qi & Luo, Chuanhai & Li, Meizhu & Deng, Yong & Mahadevan, Sankaran, 2015. "Tsallis information dimension of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 707-717.
    20. Gohar Feroz Khan & Junghoon Moon & Han Woo Park, 2011. "Network of the core: mapping and visualizing the core of scientific domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 759-779, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:57:y:2023:i:3:d:10.1007_s11135-022-01467-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.