IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v129y2024i1d10.1007_s11192-023-04884-2.html
   My bibliography  Save this article

Fine-grained classification of journal articles based on multiple layers of information through similarity network fusion: The case of the Cambridge Journal of Economics

Author

Listed:
  • Alberto Baccini

    (Università degli Studi di Siena)

  • Federica Baccini

    (Università degli Studi di Roma “La Sapienza”)

  • Lucio Barabesi

    (Università degli Studi di Siena)

  • Martina Cioni

    (Università degli Studi di Siena)

  • Eugenio Petrovich

    (Università degli Studi di Torino)

  • Daria Pignalosa

    (Università degli Studi di Siena)

Abstract

In order to explore the suitability of a fine-grained classification of journal articles by exploiting multiple sources of information, articles are organized in a two-layer multiplex. The first layer conveys similarities based on the full-text of articles, and the second similarities based on cited references. The information of the two layers are only weakly associated. The Similarity Network Fusion process is adopted to combine the two layers into a new single-layer network. A clustering algorithm is applied to the fused network and the classification of articles is obtained. In order to evaluate its coherence, this classification is compared with the ones obtained by applying the same algorithm to each of two layers. Moreover, the classification obtained for the fused network is also compared with the classifications obtained when the layers of information are integrated using different methods available in literature. In the case of the Cambridge Journal of Economics, Similarity Network Fusion appears to be the best option. Moreover, the achieved classification appears to be fine-grained enough to represent the extreme heterogeneity characterizing the contributions published in the journal.

Suggested Citation

  • Alberto Baccini & Federica Baccini & Lucio Barabesi & Martina Cioni & Eugenio Petrovich & Daria Pignalosa, 2024. "Fine-grained classification of journal articles based on multiple layers of information through similarity network fusion: The case of the Cambridge Journal of Economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(1), pages 373-400, January.
  • Handle: RePEc:spr:scient:v:129:y:2024:i:1:d:10.1007_s11192-023-04884-2
    DOI: 10.1007/s11192-023-04884-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-023-04884-2
    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/s11192-023-04884-2?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. Alexandre Truc & François Claveau & Olivier Santerre, 2021. "Economic methodology: a bibliometric perspective," Journal of Economic Methodology, Taylor & Francis Journals, vol. 28(1), pages 67-78, January.
    2. Beatrice Cherrier, 2017. "Classifying Economics: A History of the JEL Codes," Journal of Economic Literature, American Economic Association, vol. 55(2), pages 545-579, June.
    3. José Edwards & Yann Giraud & Christophe Schinckus, 2018. "A quantitative turn in the historiography of economics?," Journal of Economic Methodology, Taylor & Francis Journals, vol. 25(4), pages 283-290, October.
    4. Richard Klavans & Kevin W. Boyack, 2017. "Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 984-998, April.
    5. Chaoqun Ni & Cassidy R. Sugimoto & Jiepu Jiang, 2013. "Venue-author-coupling: A measure for identifying disciplines through author communities," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(2), pages 265-279, February.
    6. Ashwani Saith, 2023. "The Cambridge Journal of Economics – A Forum of One’s Own," Review of Political Economy, Taylor & Francis Journals, vol. 35(1), pages 28-49, January.
    7. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    8. François Claveau & Yves Gingras, 2016. "Macrodynamics of Economics: A Bibliometric History," History of Political Economy, Duke University Press, vol. 48(4), pages 551-592, December.
    9. Angela Ambrosino & Mario Cedrini & John B. Davis & Stefano Fiori & Marco Guerzoni & Massimiliano Nuccio, 2018. "What topic modeling could reveal about the evolution of economics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 25(4), pages 329-348, October.
    10. Marek Omelka & Šárka Hudecová, 2013. "A comparison of the Mantel test with a generalised distance covariance test," Environmetrics, John Wiley & Sons, Ltd., vol. 24(7), pages 449-460, November.
    11. Thor, Andreas & Marx, Werner & Leydesdorff, Loet & Bornmann, Lutz, 2016. "Introducing CitedReferencesExplorer (CRExplorer): A program for reference publication year spectroscopy with cited references standardization," Journal of Informetrics, Elsevier, vol. 10(2), pages 503-515.
    12. Baccini, Federica & Barabesi, Lucio & Baccini, Alberto & Khelfaoui, Mahdi & Gingras, Yves, 2022. "Similarity network fusion for scholarly journals," Journal of Informetrics, Elsevier, vol. 16(1).
    13. M. M. Kessler, 1965. "Comparison of the results of bibliographic coupling and analytic subject indexing," American Documentation, Wiley Blackwell, vol. 16(3), pages 223-233, July.
    14. Maria Cristina Marcuzzo & Nerio Naldi & Eleonora Sanfilippo & Annalisa Rosselli, 2008. "Cambridge as a Place in Economics," History of Political Economy, Duke University Press, vol. 40(4), pages 569-593, Winter.
    15. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    16. Sjögårde, Peter & Ahlgren, Per, 2018. "Granularity of algorithmically constructed publication-level classifications of research publications: Identification of topics," Journal of Informetrics, Elsevier, vol. 12(1), pages 133-152.
    17. Kevin W. Boyack, 2017. "Investigating the effect of global data on topic detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 999-1015, May.
    18. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    19. Frizo Janssens & Wolfgang Glänzel & Bart Moor, 2008. "A hybrid mapping of information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 607-631, June.
    20. Wolfgang Glänzel & András Schubert, 2003. "A new classification scheme of science fields and subfields designed for scientometric evaluation purposes," Scientometrics, Springer;Akadémiai Kiadó, vol. 56(3), pages 357-367, March.
    21. Chaoqun Ni & Cassidy R. Sugimoto & Jiepu Jiang, 2013. "Venue‐author‐coupling: A measure for identifying disciplines through author communities," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(2), pages 265-279, February.
    22. Federica Baccini & Monica Bianchini & Filippo Geraci, 2022. "Graph-Based Integration of Histone Modification Profiles," Mathematics, MDPI, vol. 10(11), pages 1-15, May.
    23. Ahlgren, Per & Colliander, Cristian, 2009. "Document–document similarity approaches and science mapping: Experimental comparison of five approaches," Journal of Informetrics, Elsevier, vol. 3(1), pages 49-63.
    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. Sjögårde, Peter & Ahlgren, Per, 2018. "Granularity of algorithmically constructed publication-level classifications of research publications: Identification of topics," Journal of Informetrics, Elsevier, vol. 12(1), pages 133-152.
    2. Baccini, Federica & Barabesi, Lucio & Baccini, Alberto & Khelfaoui, Mahdi & Gingras, Yves, 2022. "Similarity network fusion for scholarly journals," Journal of Informetrics, Elsevier, vol. 16(1).
    3. Michel Zitt, 2015. "Meso-level retrieval: IR-bibliometrics interplay and hybrid citation-words methods in scientific fields delineation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2223-2245, March.
    4. Sitaram Devarakonda & Dmitriy Korobskiy & Tandy Warnow & George Chacko, 2020. "Viewing computer science through citation analysis: Salton and Bergmark Redux," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 271-287, October.
    5. Paul Donner, 2021. "Validation of the Astro dataset clustering solutions with external data," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1619-1645, February.
    6. Peter Sjögårde & Per Ahlgren, 2024. "Normalization of direct citations for clustering in publication-level networks: evaluation of six approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(3), pages 1949-1968, March.
    7. Urdiales, Cristina & Guzmán, Eduardo, 2024. "An automatic and association-based procedure for hierarchical publication subject categorization," Journal of Informetrics, Elsevier, vol. 18(1).
    8. Serhat Burmaoglu & Ozcan Saritas, 2019. "An evolutionary analysis of the innovation policy domain: Is there a paradigm shift?," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 823-847, March.
    9. Ying Huang & Wolfgang Glänzel & Lin Zhang, 2021. "Tracing the development of mapping knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6201-6224, July.
    10. Matthias Held & Grit Laudel & Jochen Gläser, 2021. "Challenges to the validity of topic reconstruction," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4511-4536, May.
    11. Fabian Meyer-Brötz & Edgar Schiebel & Leo Brecht, 2017. "Experimental evaluation of parameter settings in calculation of hybrid similarities: effects of first- and second-order similarity, edge cutting, and weighting factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1307-1325, June.
    12. Rey-Long Liu, 2015. "Passage-Based Bibliographic Coupling: An Inter-Article Similarity Measure for Biomedical Articles," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-22, October.
    13. Rons, Nadine, 2018. "Bibliometric approximation of a scientific specialty by combining key sources, title words, authors and references," Journal of Informetrics, Elsevier, vol. 12(1), pages 113-132.
    14. Moshe Blidstein & Maayan Zhitomirsky-Geffet, 2022. "Towards a new generic framework for citation network generation and analysis in the humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4275-4297, July.
    15. Zhang, Yi & Shang, Lining & Huang, Lu & Porter, Alan L. & Zhang, Guangquan & Lu, Jie & Zhu, Donghua, 2016. "A hybrid similarity measure method for patent portfolio analysis," Journal of Informetrics, Elsevier, vol. 10(4), pages 1108-1130.
    16. Fei Shu & Yue Ma & Junping Qiu & Vincent Larivière, 2020. "Classifications of science and their effects on bibliometric evaluations," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2727-2744, December.
    17. Jochen Gläser & Wolfgang Glänzel & Andrea Scharnhorst, 2017. "Same data—different results? Towards a comparative approach to the identification of thematic structures in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 981-998, May.
    18. Yi-Ming Wei & Jin-Wei Wang & Tianqi Chen & Bi-Ying Yu & Hua Liao, 2018. "Frontiers of Low-Carbon Technologies: Results from Bibliographic Coupling with Sliding Window," CEEP-BIT Working Papers 116, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    19. 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.
    20. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.

    More about this item

    Keywords

    Similarity network fusion; Generalized distance correlation; Partial distance correlation; Multilayer social networks; Communities in networks; Topic modeling;
    All these keywords.

    JEL classification:

    • B2 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925
    • A1 - General Economics and Teaching - - General Economics

    Statistics

    Access and download statistics

    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:scient:v:129:y:2024:i:1:d:10.1007_s11192-023-04884-2. 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.