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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
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    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. 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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Liu, Yunmei & Yang, Liu & Chen, Min, 2021. "A new citation concept: Triangular citation in the literature," Journal of Informetrics, Elsevier, vol. 15(2).
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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).
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Post-Print halshs-02080535, HAL.
    23. 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.
    24. 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.
    25. 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).
    26. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 617-641, May.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    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.
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