IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i11d10.1007_s11192-022-04401-x.html
   My bibliography  Save this article

Measuring the interdisciplinarity of Information and Library Science interactions using citation analysis and semantic analysis

Author

Listed:
  • Lu Huang

    (Beijing Institute of Technology)

  • Yijie Cai

    (Beijing Institute of Technology)

  • Erdong Zhao

    (Beijing Institute of Technology)

  • Shengting Zhang

    (Beijing Institute of Technology)

  • Yue Shu

    (Beijing Institute of Technology)

  • Jiao Fan

    (Beijing Institute of Technology)

Abstract

Interdisciplinary interaction and integration have become major features of current science and technology development. Hence, ways to measure the strength of the interdisciplinary interactions between two given disciplines has become a crucial issue. In this study, we propose a novel framework for measuring interdisciplinary interaction that is based on both citation analysis and semantic analysis. Within the framework, direct citations combined with bibliographic coupling reflect citation relationship of interdisciplinary knowledge, while an LDA model combined with a word embedding model are used to explore the integration and diffusion of knowledge via semantic similarity. The strength of the interdisciplinary interactions is then assessed with an entropy weighting method. A case study on the interactions between Information & Library Science and six other disciplines demonstrates the efficacy and reliability of the framework.

Suggested Citation

  • Lu Huang & Yijie Cai & Erdong Zhao & Shengting Zhang & Yue Shu & Jiao Fan, 2022. "Measuring the interdisciplinarity of Information and Library Science interactions using citation analysis and semantic analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6733-6761, November.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:11:d:10.1007_s11192-022-04401-x
    DOI: 10.1007/s11192-022-04401-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-022-04401-x
    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/s11192-022-04401-x?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. Kavitha Karunan & Hiran H. Lathabai & Thara Prabhakaran, 2017. "Discovering interdisciplinary interactions between two research fields using citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 335-367, October.
    2. Huang, Lu & Chen, Xiang & Ni, Xingxing & Liu, Jiarun & Cao, Xiaoli & Wang, Changtian, 2021. "Tracking the dynamics of co-word networks for emerging topic identification," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    3. 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.
    4. Alexis-Michel Mugabushaka & Anthi Kyriakou & Theo Papazoglou, 2016. "Bibliometric indicators of interdisciplinarity: the potential of the Leinster–Cobbold diversity indices to study disciplinary diversity," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 593-607, May.
    5. Leah G. Nichols, 2014. "A topic model approach to measuring interdisciplinarity at the National Science Foundation," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(3), pages 741-754, September.
    6. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 617-641, May.
    7. Benito-Santos, Alejandro & Theron, Roberto, 2019. "Cross-domain Visual Exploration of Academic Corpora via the Latent Meaning of User-authored Keywords," OSF Preprints h29qv, Center for Open Science.
    8. Zhang, Yi & Lu, Jie & Liu, Feng & Liu, Qian & Porter, Alan & Chen, Hongshu & Zhang, Guangquan, 2018. "Does deep learning help topic extraction? A kernel k-means clustering method with word embedding," Journal of Informetrics, Elsevier, vol. 12(4), pages 1099-1117.
    9. Ruobing Chi & Jonathan Young, 2013. "The interdisciplinary structure of research on intercultural relations: a co-citation network analysis study," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 147-171, July.
    10. Jian Xu & Ying Ding & Yi Bu & Shuqing Deng & Chen Yu & Yimin Zou & Andrew Madden, 2019. "Interdisciplinary scholarly communication: an exploratory study for the field of joint attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1597-1619, June.
    11. Leydesdorff, Loet & Rafols, Ismael, 2011. "Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations," Journal of Informetrics, Elsevier, vol. 5(1), pages 87-100.
    12. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
    13. 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.
    14. Liu, Yunmei & Yang, Liu & Chen, Min, 2021. "A new citation concept: Triangular citation in the literature," Journal of Informetrics, Elsevier, vol. 15(2).
    15. Lijun Yang & Liangxiu Han & Naxin Liu, 2019. "A new approach to journal co-citation matrix construction based on the number of co-cited articles in journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 507-517, August.
    16. Loet Leydesdorff, 2008. "On the normalization and visualization of author co‐citation data: Salton's Cosine versus the Jaccard index," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(1), pages 77-85, January.
    17. Kai Hu & Huayi Wu & Kunlun Qi & Jingmin Yu & Siluo Yang & Tianxing Yu & Jie Zheng & Bo Liu, 2018. "A domain keyword analysis approach extending Term Frequency-Keyword Active Index with Google Word2Vec model," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 1031-1068, March.
    18. Björn Hammarfelt, 2011. "Interdisciplinarity and the intellectual base of literature studies: citation analysis of highly cited monographs," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(3), pages 705-725, March.
    19. 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.
    20. Yu-Wei Chang & Mu-Hsuan Huang, 2012. "A study of the evolution of interdisciplinarity in library and information science: Using three bibliometric methods," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(1), pages 22-33, January.
    21. Zhang, Yi & Porter, Alan L. & Hu, Zhengyin & Guo, Ying & Newman, Nils C., 2014. "“Term clumping” for technical intelligence: A case study on dye-sensitized solar cells," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 26-39.
    22. Xiao Zhou & Lu Huang & Yi Zhang & Miaomiao Yu, 2019. "A hybrid approach to detecting technological recombination based on text mining and patent network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 699-737, November.
    23. Haiyun Xu & Ting Guo & Zenghui Yue & Lijie Ru & Shu Fang, 2016. "Interdisciplinary topics of information science: a study based on the terms interdisciplinarity index series," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 583-601, February.
    24. Lili Wang & Ad Notten & Alexandru Surpatean, 2013. "Interdisciplinarity of nano research fields: a keyword mining approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 877-892, March.
    25. Kun Lu & Dietmar Wolfram, 2012. "Measuring author research relatedness: A comparison of word-based, topic-based, and author cocitation approaches," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(10), pages 1973-1986, October.
    26. 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.
    27. Yan Wang & Zhiyuan Liu & Maosong Sun, 2015. "Incorporating Linguistic Knowledge for Learning Distributed Word Representations," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-20, April.
    28. Wang, Xuefeng & Zhang, Shuo & Liu, Yuqin & Du, Jian & Huang, Heng, 2021. "How pharmaceutical innovation evolves: The path from science to technological development to marketable drugs," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    29. Shengli Deng & Sudi Xia, 2020. "Mapping the interdisciplinarity in information behavior research: a quantitative study using diversity measure and co-occurrence analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 489-513, July.
    30. Mu-Hsuan Huang & Yu-Wei Chang, 2012. "A comparative study of interdisciplinary changes between information science and library science," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 789-803, June.
    31. Munui Kim & Injun Baek & Min Song, 2018. "Topic diffusion analysis of a weighted citation network in biomedical literature," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(2), pages 329-342, February.
    32. Wagner, Caroline S. & Roessner, J. David & Bobb, Kamau & Klein, Julie Thompson & Boyack, Kevin W. & Keyton, Joann & Rafols, Ismael & Börner, Katy, 2011. "Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature," Journal of Informetrics, Elsevier, vol. 5(1), pages 14-26.
    33. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Post-Print halshs-02080535, HAL.
    34. Yu‐Wei Chang & Mu‐Hsuan Huang, 2012. "A study of the evolution of interdisciplinarity in library and information science: Using three bibliometric methods," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(1), pages 22-33, January.
    35. Scott Deerwester & Susan T. Dumais & George W. Furnas & Thomas K. Landauer & Richard Harshman, 1990. "Indexing by latent semantic analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 391-407, September.
    36. Kun Lu & Dietmar Wolfram, 2012. "Measuring author research relatedness: A comparison of word‐based, topic‐based, and author cocitation approaches," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(10), pages 1973-1986, October.
    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. Yi Zhang & Chengzhi Zhang & Philipp Mayr & Arho Suominen, 2022. "An editorial of “AI + informetrics”: multi-disciplinary interactions in the era of big data," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6503-6507, November.
    2. Guoyang Rong & Changling Li & Zhijian Zhang & Shuaipu Chen & Yuxing Qian, 2024. "Investigating the application of work–energy metaphor in interdisciplinary citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3573-3591, 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. Wang, Shiyun & Mao, Jin & Lu, Kun & Cao, Yujie & Li, Gang, 2021. "Understanding interdisciplinary knowledge integration through citance analysis: A case study on eHealth," Journal of Informetrics, Elsevier, vol. 15(4).
    2. Wolfgang Glänzel & Koenraad Debackere, 2022. "Various aspects of interdisciplinarity in research and how to quantify and measure those," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5551-5569, September.
    3. Zhichao Ba & Yujie Cao & Jin Mao & Gang Li, 2019. "A hierarchical approach to analyzing knowledge integration between two fields—a case study on medical informatics and computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1455-1486, June.
    4. Hongyu Zhou & Raf Guns & Tim C. E. Engels, 2022. "Are social sciences becoming more interdisciplinary? Evidence from publications 1960–2014," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(9), pages 1201-1221, September.
    5. Chen, Shiji & Qiu, Junping & Arsenault, Clément & Larivière, Vincent, 2021. "Exploring the interdisciplinarity patterns of highly cited papers," Journal of Informetrics, Elsevier, vol. 15(1).
    6. 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.
    7. Shiyun Wang & Jin Mao & Yujie Cao & Gang Li, 2022. "Integrated knowledge content in an interdisciplinary field: identification, classification, and application," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6581-6614, November.
    8. Sander Zwanenburg & Maryam Nakhoda & Peter Whigham, 2022. "Toward greater consistency and validity in measuring interdisciplinarity: a systematic and conceptual evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7769-7788, December.
    9. Shengli Deng & Sudi Xia, 2020. "Mapping the interdisciplinarity in information behavior research: a quantitative study using diversity measure and co-occurrence analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 489-513, July.
    10. Lu Huang & Xiang Chen & Yi Zhang & Changtian Wang & Xiaoli Cao & Jiarun Liu, 2022. "Identification of topic evolution: network analytics with piecewise linear representation and word embedding," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5353-5383, September.
    11. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 617-641, May.
    12. 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.
    13. Xuefeng Wang & Zhinan Wang & Ying Huang & Yun Chen & Yi Zhang & Huichao Ren & Rongrong Li & Jinhui Pang, 2017. "Measuring interdisciplinarity of a research system: detecting distinction between publication categories and citation categories," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 2023-2039, June.
    14. Lin Zhang & Beibei Sun & Zaida Chinchilla-Rodríguez & Lixin Chen & Ying Huang, 2018. "Interdisciplinarity and collaboration: on the relationship between disciplinary diversity in departmental affiliations and reference lists," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 271-291, October.
    15. Fan, Yangliu & Lehmann, Sune & Blok, Anders, 2022. "Extracting the interdisciplinary specialty structures in social media data-based research: A clustering-based network approach," Journal of Informetrics, Elsevier, vol. 16(3).
    16. Wooseok Jang & Heeyeul Kwon & Yongtae Park & Hakyeon Lee, 2018. "Predicting the degree of interdisciplinarity in academic fields: the case of nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 231-254, July.
    17. Ryo Takahashi & Kenji Kaibe & Kazuyuki Suzuki & Sayaka Takahashi & Kotaro Takeda & Marc Hansen & Michiaki Yumoto, 2023. "New concept of the affinity between research fields using academic journal data in Scopus," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3507-3534, June.
    18. 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.
    19. 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.
    20. Jian Xu & Yi Bu & Ying Ding & Sinan Yang & Hongli Zhang & Chen Yu & Lin Sun, 2018. "Understanding the formation of interdisciplinary research from the perspective of keyword evolution: a case study on joint attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 973-995, November.

    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:127:y:2022:i:11:d:10.1007_s11192-022-04401-x. 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.