IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v13y2019i1p202-225.html
   My bibliography  Save this article

Comparing journal and paper level classifications of science

Author

Listed:
  • Shu, Fei
  • Julien, Charles-Antoine
  • Zhang, Lin
  • Qiu, Junping
  • Zhang, Jing
  • Larivière, Vincent

Abstract

The classification of science into disciplines is at the heart of bibliometric analyses. While most classifications systems are implemented at the journal level, their accuracy has been questioned, and paper-level classifications have been considered by many to be more precise. However, few studies investigated the difference between journal and the paper classification systems. This study addresses this gap by comparing the journal- and paper-level classifications for the same set of papers and journals. This isolates the effects of classification precision (i.e., journal- or paper-level) to reveal the extent of paper misclassification. Results show almost half of papers could be misclassified in journal classification systems. Given their importance in the construction and analysis of bibliometric indicators, more attention should be given to the robustness and accuracy of these disciplinary classifications schemes.

Suggested Citation

  • Shu, Fei & Julien, Charles-Antoine & Zhang, Lin & Qiu, Junping & Zhang, Jing & Larivière, Vincent, 2019. "Comparing journal and paper level classifications of science," Journal of Informetrics, Elsevier, vol. 13(1), pages 202-225.
    • Handle: RePEc:eee:infome:v:13:y:2019:i:1:p:202-225
    DOI: 10.1016/j.joi.2018.12.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157718303298
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2018.12.005?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. Bihui Jin & Bing Wang, 1999. "Chinese science citation database: Its construction and application," Scientometrics, Springer;Akadémiai Kiadó, vol. 45(2), pages 325-332, June.
    2. Heather Keathley-Herring & Eileen Van Aken & Fernando Gonzalez-Aleu & Fernando Deschamps & Geert Letens & Pablo Cardenas Orlandini, 2016. "Assessing the maturity of a research area: bibliometric review and proposed framework," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 927-951, November.
    3. Lin Zhang & Frizo Janssens & Liming Liang & Wolfgang Glänzel, 2010. "Journal cross-citation analysis for validation and improvement of journal-based subject classification in bibliometric research," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(3), pages 687-706, March.
    4. 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.
    5. 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.
    6. Alexander I. Pudovkin & Eugene Garfield, 2002. "Algorithmic procedure for finding semantically related journals," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 53(13), pages 1113-1119, November.
    7. 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.
    8. Klavans, Richard & Boyack, Kevin W., 2017. "Research portfolio analysis and topic prominence," Journal of Informetrics, Elsevier, vol. 11(4), pages 1158-1174.
    9. 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.
    10. Boyack, Kevin W. & Klavans, Richard, 2014. "Including cited non-source items in a large-scale map of science: What difference does it make?," Journal of Informetrics, Elsevier, vol. 8(3), pages 569-580.
    11. Ming-Chao Huang & Shih-Chieh Fang & Shao-Chi Chang, 2011. "Tracking R&D behavior: bibliometric analysis of drug patents in the Orange Book," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(3), pages 805-818, September.
    12. Kevin W. Boyack & Richard Klavans, 2014. "Creation of a highly detailed, dynamic, global model and map of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 670-685, April.
    13. Ismael Rafols & Loet Leydesdorff, 2009. "Content‐based and algorithmic classifications of journals: Perspectives on the dynamics of scientific communication and indexer effects," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(9), pages 1823-1835, September.
    14. Yuen-Hsien Tseng & Ming-Yueh Tsay, 2013. "Journal clustering of library and information science for subfield delineation using the bibliometric analysis toolkit: CATAR," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 503-528, May.
    15. Ludo Waltman & Nees Jan van Eck, 2012. "A new methodology for constructing a publication‐level classification system of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    16. 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.
    17. Chi, Pei-Shan, 2016. "Differing disciplinary citation concentration patterns of book and journal literature?," Journal of Informetrics, Elsevier, vol. 10(3), pages 814-829.
    18. 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.
    19. Vincent Larivière & Yves Gingras & Éric Archambault, 2009. "The decline in the concentration of citations, 1900–2007," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(4), pages 858-862, April.
    20. Loet Leydesdorff & Lutz Bornmann, 2016. "The operationalization of “fields” as WoS subject categories (WCs) in evaluative bibliometrics: The cases of “library and information science” and “science & technology studies”," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(3), pages 707-714, March.
    21. Shu, Fei & Dinneen, Jesse David & Asadi, Banafsheh & Julien, Charles-Antoine, 2017. "Mapping science using Library of Congress Subject Headings," Journal of Informetrics, Elsevier, vol. 11(4), pages 1080-1094.
    22. Loet Leydesdorff & Ismael Rafols, 2009. "A global map of science based on the ISI subject categories," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(2), pages 348-362, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammad Imran Qureshi & Nohman Khan & Shazia Qayyum & Subha Malik & Sanil S Hishan & Thurasamy Ramayah, 2020. "Classifications of Sustainable Manufacturing Practices in ASEAN Region: A Systematic Review and Bibliometric Analysis of the Past Decade of Research," Sustainability, MDPI, vol. 12(21), pages 1-19, October.
    2. Ugo Moschini & Elena Fenialdi & Cinzia Daraio & Giancarlo Ruocco & Elisa Molinari, 2020. "A comparison of three multidisciplinarity indices based on the diversity of Scopus subject areas of authors’ documents, their bibliography and their citing papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1145-1158, November.
    3. Gerson Pech & Catarina Delgado & Silvio Paolo Sorella, 2022. "Classifying papers into subfields using Abstracts, Titles, Keywords and KeyWords Plus through pattern detection and optimization procedures: An application in Physics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(11), pages 1513-1528, November.
    4. Fei Shu & Jesse David Dinneen & Shiji Chen, 2022. "Measuring the disparity among scientific disciplines using Library of Congress Subject Headings," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3613-3628, June.
    5. Yashan Li & Jinge Mao & Lin Zhang & Dongbo Wang & Si Shen & Ying Huang, 2022. "How scientific research incorporates policy: an examination using the case of China’s science and technology evaluation system," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5283-5306, September.
    6. Fei Shu & Xiaojian Wang & Sichen Liu & Junping Qiu & Vincent Larivière, 2023. "Global impact or national accessibility? A paradox in China’s science," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 263-277, January.
    7. Muñoz-Écija, Teresa & Vargas-Quesada, Benjamín & Chinchilla Rodríguez, Zaida, 2019. "Coping with methods for delineating emerging fields: Nanoscience and nanotechnology as a case study," Journal of Informetrics, Elsevier, vol. 13(4).
    8. Kaile Gong, 2023. "The influence of discipline consistency between papers and published journals on citations: an analysis of Chinese papers in three social science disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3129-3146, May.
    9. Lin Zhang & Beibei Sun & Fei Shu & Ying Huang, 2022. "Comparing paper level classifications across different methods and systems: an investigation of Nature publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7633-7651, December.
    10. Rodrigo Dorantes-Gilardi & Aurora A. Ramírez-Álvarez & Diana Terrazas-Santamaría, 2023. "Is there a differentiated gender effect of collaboration with super-cited authors? Evidence from junior researchers in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2317-2336, April.
    11. Michael Gusenbauer, 2022. "Search where you will find most: Comparing the disciplinary coverage of 56 bibliographic databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2683-2745, May.
    12. Ayelet Gal-Tzur & Sivan Albagli-Kim, 2023. "Systematic Analysis of the Literature Addressing the Use of Machine Learning Techniques in Transportation—A Methodology and Its Application," Sustainability, MDPI, vol. 16(1), pages 1-19, December.
    13. Shannon Mason & Lenandlar Singh, 2022. "When a journal is both at the ‘top’ and the ‘bottom’: the illogicality of conflating citation-based metrics with quality," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3683-3694, June.
    14. Guo Chen & Jing Chen & Yu Shao & Lu Xiao, 2023. "Automatic noise reduction of domain-specific bibliographic datasets using positive-unlabeled learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1187-1204, February.
    15. Andrea Bonaccorsi & Nicola Melluso & Francesco Alessandro Massucci, 2022. "Exploring the antecedents of interdisciplinarity at the European Research Council: a topic modeling approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 6961-6991, December.
    16. 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.
    17. Paul Donner, 2021. "Validation of the Astro dataset clustering solutions with external data," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1619-1645, February.
    18. Baccini, Federica & Barabesi, Lucio & Baccini, Alberto & Khelfaoui, Mahdi & Gingras, Yves, 2022. "Similarity network fusion for scholarly journals," Journal of Informetrics, Elsevier, vol. 16(1).
    19. Kaile Gong & Ying Cheng, 2022. "Patterns and impact of collaboration in China’s social sciences: cross-database comparisons between CSSCI and SSCI," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5947-5964, October.
    20. Shir Aviv-Reuven & Ariel Rosenfeld, 2023. "A logical set theory approach to journal subject classification analysis: intra-system irregularities and inter-system discrepancies in Web of Science and Scopus," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 157-175, January.
    21. 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.
    22. Gabriele Sampagnaro, 2023. "Keyword occurrences and journal specialization," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5629-5645, October.
    23. Kai Li & Chenyue Jiao, 2022. "The data paper as a sociolinguistic epistemic object: A content analysis on the rhetorical moves used in data paper abstracts," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(6), pages 834-846, June.
    24. Cao, Renmeng & Geng, Yu & Xu, Xiaoke & Wang, Xianwen, 2022. "How does duplicate tweeting boost social media exposure to scholarly articles?," Journal of Informetrics, Elsevier, vol. 16(1).

    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 & Beibei Sun & Fei Shu & Ying Huang, 2022. "Comparing paper level classifications across different methods and systems: an investigation of Nature publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7633-7651, December.
    2. 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.
    3. Wang, Qi & Waltman, Ludo, 2016. "Large-scale analysis of the accuracy of the journal classification systems of Web of Science and Scopus," Journal of Informetrics, Elsevier, vol. 10(2), pages 347-364.
    4. 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.
    5. Leydesdorff, Loet & Bornmann, Lutz & Zhou, Ping, 2016. "Construction of a pragmatic base line for journal classifications and maps based on aggregated journal-journal citation relations," Journal of Informetrics, Elsevier, vol. 10(4), pages 902-918.
    6. Juan Miguel Campanario, 2018. "Are leaders really leading? Journals that are first in Web of Science subject categories in the context of their groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 111-130, April.
    7. Muñoz-Écija, Teresa & Vargas-Quesada, Benjamín & Chinchilla Rodríguez, Zaida, 2019. "Coping with methods for delineating emerging fields: Nanoscience and nanotechnology as a case study," Journal of Informetrics, Elsevier, vol. 13(4).
    8. 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.
    9. Gómez-Núñez, Antonio J. & Batagelj, Vladimir & Vargas-Quesada, Benjamín & Moya-Anegón, Félix & Chinchilla-Rodríguez, Zaida, 2014. "Optimizing SCImago Journal & Country Rank classification by community detection," Journal of Informetrics, Elsevier, vol. 8(2), pages 369-383.
    10. Loet Leydesdorff & Lutz Bornmann & Caroline S. Wagner, 2017. "Generating clustered journal maps: an automated system for hierarchical classification," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1601-1614, March.
    11. 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.
    12. Wolfram, Dietmar & Zhao, Yuehua, 2014. "A comparison of journal similarity across six disciplines using citing discipline analysis," Journal of Informetrics, Elsevier, vol. 8(4), pages 840-853.
    13. Ricardo Arencibia-Jorge & Rosa Lidia Vega-Almeida & José Luis Jiménez-Andrade & Humberto Carrillo-Calvet, 2022. "Evolutionary stages and multidisciplinary nature of artificial intelligence research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5139-5158, September.
    14. Nees Jan Eck & Ludo Waltman, 2017. "Citation-based clustering of publications using CitNetExplorer and VOSviewer," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1053-1070, May.
    15. Carlos Olmeda-Gómez & Carlos Romá-Mateo & Maria-Antonia Ovalle-Perandones, 2019. "Overview of trends in global epigenetic research (2009–2017)," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1545-1574, June.
    16. Loet Leydesdorff & Caroline S. Wagner & Lutz Bornmann, 2018. "Betweenness and diversity in journal citation networks as measures of interdisciplinarity—A tribute to Eugene Garfield," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 567-592, February.
    17. 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.
    18. Li, Menghui & Yang, Liying & Zhang, Huina & Shen, Zhesi & Wu, Chensheng & Wu, Jinshan, 2017. "Do mathematicians, economists and biomedical scientists trace large topics more strongly than physicists?," Journal of Informetrics, Elsevier, vol. 11(2), pages 598-607.
    19. 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.
    20. 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.

    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:eee:infome:v:13:y:2019:i:1:p:202-225. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    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.