IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i11d10.1007_s11192-021-04190-9.html
   My bibliography  Save this article

ITGInsight–discovering and visualizing research fronts in the scientific literature

Author

Listed:
  • Xuefeng Wang

    (Beijing Institute of Technology)

  • Shuo Zhang

    (Beijing Institute of Technology)

  • Yuqin liu

    (Beijing Institute of Graphic Communication)

Abstract

Nowadays, most organizations face the challenge of having to track the latest technological developments so as to discover new technology opportunities and to identify threats in their competitive environment. The capacity to do this relies heavily on the ability to recognize scientific innovation. Hence, monitoring emerging research directions in the scientific literature has become an important task for both researchers and policy makers. Yet the best method of doing so is still a topic of controversy. Our goal is to develop a generic computational framework that can describe a research domain in terms of its research fronts and further track the evolution trends of the knowledge structures behind each research front for the purposes of identifying knowledge innovation. The results show the evolution trends of knowledge structures could lead up to pioneering research. Implemented in ITGInsight, a C# application, the modelling and visualization process incorporates a topic clustering model and a topic evolution model to reveal knowledge structures and their evolution trends. Using the framework in a case study on synthetic biology, we verified the results it produced by consulting the literature and a panel of domain experts. The tool proves to be powerful font of insightful information that would be difficult and time-consuming for researchers and policy makers to gather on their own. Anyone involved in R&D planning, research funds allocation, and technology opportunity analysis will find the framework useful.

Suggested Citation

  • Xuefeng Wang & Shuo Zhang & Yuqin liu, 2022. "ITGInsight–discovering and visualizing research fronts in the scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6509-6531, November.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:11:d:10.1007_s11192-021-04190-9
    DOI: 10.1007/s11192-021-04190-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-021-04190-9
    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/s11192-021-04190-9?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. Yongho Lee & So Young Kim & Inseok Song & Yongtae Park & Juneseuk Shin, 2014. "Technology opportunity identification customized to the technological capability of SMEs through two-stage patent analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 227-244, July.
    2. Xianwen Wang & Zhi Wang & Shenmeng Xu, 2013. "Tracing scientist’s research trends realtimely," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 717-729, May.
    3. M.J. Cobo & A.G. López‐Herrera & E. Herrera‐Viedma & F. Herrera, 2012. "SciMAT: A new science mapping analysis software tool," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(8), pages 1609-1630, August.
    4. Lee, Jeongjin & Kim, Changseok & Shin, Juneseuk, 2017. "Technology opportunity discovery to R&D planning: Key technological performance analysis," Technological Forecasting and Social Change, Elsevier, vol. 119(C), pages 53-63.
    5. 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.
    6. Xuefeng Wang & Rongrong Li & Shiming Ren & Donghua Zhu & Meng Huang & Pengjun Qiu, 2014. "Collaboration network and pattern analysis: case study of dye-sensitized solar cells," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1745-1762, March.
    7. Jun Chen & Lingling Yang, 2021. "A Bibliometric Review of Volatility Spillovers in Financial Markets: Knowledge Bases and Research Fronts," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(5), pages 1358-1379, April.
    8. Ying Huang & Yi Zhang & Jing Ma & Alan L. Porter & Xuefeng Wang & Ying Guo, 2016. "Generating Competitive Technical Intelligence Using Topical Analysis, Patent Citation Analysis, and Term Clumping Analysis," Innovation, Technology, and Knowledge Management, in: Tugrul U. Daim & Denise Chiavetta & Alan L. Porter & Ozcan Saritas (ed.), Anticipating Future Innovation Pathways Through Large Data Analysis, chapter 0, pages 153-172, Springer.
    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. 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).
    11. Henry Small, 2006. "Tracking and predicting growth areas in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 595-610, September.
    12. Jennifer Keiser & Jürg Utzinger, 2005. "Trends in the core literature on tropical medicine: a bibliometric analysis from 1952-2002," Scientometrics, Springer;Akadémiai Kiadó, vol. 62(3), pages 351-365, March.
    13. Yoon, Byungun & Park, Inchae & Coh, Byoung-youl, 2014. "Exploring technological opportunities by linking technology and products: Application of morphology analysis and text mining," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 287-303.
    14. Yoon, Janghyeok & Park, Hyunseok & Seo, Wonchul & Lee, Jae-Min & Coh, Byoung-youl & Kim, Jonghwa, 2015. "Technology opportunity discovery (TOD) from existing technologies and products: A function-based TOD framework," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 153-167.
    15. Tijssen, Robert J. W., 2002. "Science dependence of technologies: evidence from inventions and their inventors," Research Policy, Elsevier, vol. 31(4), pages 509-526, May.
    16. Vincent C. Ma & John S. Liu, 2016. "Exploring the research fronts and main paths of literature: a case study of shareholder activism research," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 33-52, October.
    17. Dangzhi Zhao & Andreas Strotmann, 2014. "The knowledge base and research front of information science 2006–2010: An author cocitation and bibliographic coupling analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 995-1006, May.
    18. Zhigao Liu & Yimei Yin & Weidong Liu & Michael Dunford, 2015. "Visualizing the intellectual structure and evolution of innovation systems research: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 135-158, April.
    19. Fiona M. Behan & Francesco Iorio & Gabriele Picco & Emanuel Gonçalves & Charlotte M. Beaver & Giorgia Migliardi & Rita Santos & Yanhua Rao & Francesco Sassi & Marika Pinnelli & Rizwan Ansari & Sarah H, 2019. "Prioritization of cancer therapeutic targets using CRISPR–Cas9 screens," Nature, Nature, vol. 568(7753), pages 511-516, April.
    20. 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.
    21. Steven A. Morris & G. Yen & Zheng Wu & Benyam Asnake, 2003. "Time line visualization of research fronts," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 413-422, March.
    22. Shaodong Xie & Jing Zhang & Yuh-Shan Ho, 2008. "Assessment of world aerosol research trends by bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 77(1), pages 113-130, October.
    23. M.J. Cobo & A.G. López-Herrera & E. Herrera-Viedma & F. Herrera, 2012. "SciMAT: A new science mapping analysis software tool," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(8), pages 1609-1630, August.
    24. Mu-Hsuan Huang & Chia-Pin Chang, 2014. "Detecting research fronts in OLED field using bibliographic coupling with sliding window," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1721-1744, March.
    25. Olle Persson, 1994. "The intellectual base and research fronts of JASIS 1986–1990," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 45(1), pages 31-38, January.
    26. Naoki Shibata & Yuya Kajikawa & Yoshiyuki Takeda & Katsumori Matsushima, 2009. "Comparative study on methods of detecting research fronts using different types of citation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(3), pages 571-580, March.
    27. S. Phineas Upham & Henry Small, 2010. "Emerging research fronts in science and technology: patterns of new knowledge development," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(1), pages 15-38, April.
    28. Bei-Ni Yan & Tian-Shyug Lee & Tsung-Pei Lee, 2015. "Mapping the intellectual structure of the Internet of Things (IoT) field (2000–2014): a co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 1285-1300, November.
    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. Ruinan Li & Raf Guns & Tim C. E. Engels & Lin Zhang & Ying Huang, 2023. "Tracking the featured topics of the International Science of Team Science conference series and their evolution during 2010–2019," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2447-2469, April.

    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. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    2. Mu-Hsuan Huang & Chia-Pin Chang, 2016. "A comparative study on three citation windows for detecting research fronts," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1835-1853, December.
    3. 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.
    4. 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.
    5. Liu, Xiang & Jiang, Tingting & Ma, Feicheng, 2013. "Collective dynamics in knowledge networks: Emerging trends analysis," Journal of Informetrics, Elsevier, vol. 7(2), pages 425-438.
    6. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    7. Xu, Shuo & Hao, Liyuan & An, Xin & Yang, Guancan & Wang, Feifei, 2019. "Emerging research topics detection with multiple machine learning models," Journal of Informetrics, Elsevier, vol. 13(4).
    8. 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.
    9. R. Fileto Maciel & P. Saskia Bayerl & Marta Macedo Kerr Pinheiro, 2019. "Technical research innovations of the US national security system," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 539-565, August.
    10. 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.
    11. Liu, Yunmei & Yang, Liu & Chen, Min, 2021. "A new citation concept: Triangular citation in the literature," Journal of Informetrics, Elsevier, vol. 15(2).
    12. Mu-Hsuan Huang & Chia-Pin Chang, 2014. "Detecting research fronts in OLED field using bibliographic coupling with sliding window," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1721-1744, March.
    13. Mu-hsuan Huang & Chia-Pin Chang, 2015. "A comparative study on detecting research fronts in the organic light-emitting diode (OLED) field using bibliographic coupling and co-citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2041-2057, March.
    14. Naeini, Ali Bonyadi & Zamani, Mehdi & Daim, Tugrul U. & Sharma, Mahak & Yalcin, Haydar, 2022. "Conceptual structure and perspectives on “innovation management”: A bibliometric review," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    15. Alfonso Ávila-Robinson & Shintaro Sengoku, 2017. "Tracing the knowledge-building dynamics in new stem cell technologies through techno-scientific networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1691-1720, September.
    16. Kyuwoong Kim & Kyeongmin Park & Sungjoo Lee, 2019. "Investigating technology opportunities: the use of SAOx analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 45-70, January.
    17. Zamani, Mehdi & Yalcin, Haydar & Naeini, Ali Bonyadi & Zeba, Gordana & Daim, Tugrul U, 2022. "Developing metrics for emerging technologies: identification and assessment," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    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. 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.

    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_s11192-021-04190-9. 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.