IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0187762.html
   My bibliography  Save this article

Understanding disciplinary vocabularies using a full-text enabled domain-independent term extraction approach

Author

Listed:
  • Erjia Yan
  • Jake Williams
  • Zheng Chen

Abstract

Publication metadata help deliver rich analyses of scholarly communication. However, research concepts and ideas are more effectively expressed through unstructured fields such as full texts. Thus, the goals of this paper are to employ a full-text enabled method to extract terms relevant to disciplinary vocabularies, and through them, to understand the relationships between disciplines. This paper uses an efficient, domain-independent term extraction method to extract disciplinary vocabularies from a large multidisciplinary corpus of PLoS ONE publications. It finds a power-law pattern in the frequency distributions of terms present in each discipline, indicating a semantic richness potentially sufficient for further study and advanced analysis. The salient relationships amongst these vocabularies become apparent in application of a principal component analysis. For example, Mathematics and Computer and Information Sciences were found to have similar vocabulary use patterns along with Engineering and Physics; while Chemistry and the Social Sciences were found to exhibit contrasting vocabulary use patterns along with the Earth Sciences and Chemistry. These results have implications to studies of scholarly communication as scholars attempt to identify the epistemological cultures of disciplines, and as a full text-based methodology could lead to machine learning applications in the automated classification of scholarly work according to disciplinary vocabularies.

Suggested Citation

  • Erjia Yan & Jake Williams & Zheng Chen, 2017. "Understanding disciplinary vocabularies using a full-text enabled domain-independent term extraction approach," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-16, November.
    • Handle: RePEc:plo:pone00:0187762
    DOI: 10.1371/journal.pone.0187762
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0187762
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0187762&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0187762?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
    ---><---

    References listed on IDEAS

    as
    1. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    2. Kevin W. Boyack & Richard Klavans & Katy Börner, 2005. "Mapping the backbone of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(3), pages 351-374, August.
    3. Graeme Hirst, 1978. "Discipline impact factors: A method for determining core journal lists," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 29(4), pages 171-172, July.
    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. Xiaoguang Wang & Hongyu Wang & Han Huang, 2021. "Evolutionary exploration and comparative analysis of the research topic networks in information disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4991-5017, June.

    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. Jianhua Hou, 2017. "Exploration into the evolution and historical roots of citation analysis by referenced publication year spectroscopy," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1437-1452, March.
    2. 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.
    3. 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.
    4. Nieminen, Paavo & Pölönen, Ilkka & Sipola, Tuomo, 2013. "Research literature clustering using diffusion maps," Journal of Informetrics, Elsevier, vol. 7(4), pages 874-886.
    5. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    6. Liming Zhao & Chenli Yin, 2024. "Driving corporate social responsibility to be innovative: Insights from a systematic literature review," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(5), pages 4115-4132, September.
    7. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 617-641, May.
    8. Zehra Taşkın & Arsev U. Aydinoglu, 2015. "Collaborative interdisciplinary astrobiology research: a bibliometric study of the NASA Astrobiology Institute," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 1003-1022, June.
    9. Henry Small, 2010. "Maps of science as interdisciplinary discourse: co-citation contexts and the role of analogy," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 835-849, June.
    10. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    11. Erjia Yan, 2014. "Topic-based Pagerank: toward a topic-level scientific evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 407-437, August.
    12. Sun, Xiaoling & Ding, Kun & Lin, Yuan, 2016. "Mapping the evolution of scientific fields based on cross-field authors," Journal of Informetrics, Elsevier, vol. 10(3), pages 750-761.
    13. Kevin W. Boyack & Katy Börner & Richard Klavans, 2009. "Mapping the structure and evolution of chemistry research," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(1), pages 45-60, April.
    14. Seyedghorban, Zahra & Matanda, Margaret Jekanyika & LaPlaca, Peter, 2016. "Advancing theory and knowledge in the business-to-business branding literature," Journal of Business Research, Elsevier, vol. 69(8), pages 2664-2677.
    15. Hu, Xiaojun & Rousseau, Ronald & Chen, Jin, 2011. "Time series of outgrow indices," Journal of Informetrics, Elsevier, vol. 5(3), pages 413-421.
    16. Pin Li & Guoli Yang & Chuanqi Wang, 2019. "Visual topical analysis of library and information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1753-1791, December.
    17. Dan Liu & Siqi Che & Wenzhong Zhu, 2022. "Visualizing the Knowledge Domain of Academic Mobility Research from 2010 to 2020: A Bibliometric Analysis Using CiteSpace," SAGE Open, , vol. 12(1), pages 21582440211, January.
    18. Yoshiyuki Takeda & Yuya Kajikawa, 2010. "Tracking modularity in citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 783-792, June.
    19. McLevey, John & McIlroy-Young, Reid, 2017. "Introducing metaknowledge: Software for computational research in information science, network analysis, and science of science," Journal of Informetrics, Elsevier, vol. 11(1), pages 176-197.
    20. Tingcan Ma & Ruinan Li & Guiyan Ou & Mingliang Yue, 2018. "Topic based research competitiveness evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 789-803, November.

    More about this item

    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:plo:pone00:0187762. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.