IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v16y2022i1s1751157721001139.html
   My bibliography  Save this article

Exploring scientific trajectories of a large-scale dataset using topic-integrated path extraction

Author

Listed:
  • Kim, Erin H.J.
  • Jeong, Yoo Kyung
  • Kim, YongHwan
  • Song, Min

Abstract

Main path analysis (MPA) is the most widely accepted approach to tracing knowledge transfer in a research field. In this study, we extracted multiple longest paths from the multidisciplinary academic field's citation network and integrating topic modeling to the extracted paths. We consider three main aspects of trajectory analysis when analyzing the represented documents through the extracted paths: emergence, authority, and topic dynamics. For path extraction, we adopt the longest path algorithm that consists of the following three steps: 1) topological sort, 2) edge relaxation, and 3) multiple path extraction. For topic integration into multiple paths, we employ latent Dirichlet allocation (LDA) by utilizing the topic-document matrix that LDA derives to select an article's topic from the citation network, where each article is labeled with the topic that is assigned with the highest topical probability for that article. We conduct a series of experiments to examine the results on a dataset from the field of healthcare informatics that PubMed provides.

Suggested Citation

  • Kim, Erin H.J. & Jeong, Yoo Kyung & Kim, YongHwan & Song, Min, 2022. "Exploring scientific trajectories of a large-scale dataset using topic-integrated path extraction," Journal of Informetrics, Elsevier, vol. 16(1).
    • Handle: RePEc:eee:infome:v:16:y:2022:i:1:s1751157721001139
    DOI: 10.1016/j.joi.2021.101242
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157721001139
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2021.101242?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. Calero-Medina, Clara & Noyons, Ed C.M., 2008. "Combining mapping and citation network analysis for a better understanding of the scientific development: The case of the absorptive capacity field," Journal of Informetrics, Elsevier, vol. 2(4), pages 272-279.
    2. Epicoco, Marianna & Oltra, Vanessa & Maïder Saint, Jean, 2014. "Knowledge dynamics and sources of eco-innovation: Mapping the Green Chemistry community," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 388-402.
    3. Stephen G. Pauker & Susan P. Pauker & Barbara J. McNeil, 1981. "The Effect of Private Attitudes on Public Policy," Medical Decision Making, , vol. 1(2), pages 103-114, June.
    4. Louis Y. Y. Lu & John S. Liu, 2013. "An innovative approach to identify the knowledge diffusion path: the case of resource-based theory," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 225-246, January.
    5. Chung-Huei Kuan, 2020. "Regarding weight assignment algorithms of main path analysis and the conversion of arc weights to node weights," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 775-782, July.
    6. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    7. Arianna Martinelli & Önder Nomaler, 2014. "Measuring knowledge persistence: a genetic approach to patent citation networks," Journal of Evolutionary Economics, Springer, vol. 24(3), pages 623-652, July.
    8. Martinelli, Arianna, 2012. "An emerging paradigm or just another trajectory? Understanding the nature of technological changes using engineering heuristics in the telecommunications switching industry," Research Policy, Elsevier, vol. 41(2), pages 414-429.
    9. Woondong Yeo & Seonho Kim & Jae-Min Lee & Jaewoo Kang, 2014. "Aggregative and stochastic model of main path identification: a case study on graphene," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 633-655, January.
    10. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    11. 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.
    12. Dejian Yu & Libo Sheng, 2020. "Knowledge diffusion paths of blockchain domain: the main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 471-497, October.
    13. Bart Verspagen, 2007. "Mapping Technological Trajectories As Patent Citation Networks: A Study On The History Of Fuel Cell Research," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 93-115.
    14. Diana Lucio‐Arias & Loet Leydesdorff, 2008. "Main‐path analysis and path‐dependent transitions in HistCite™‐based historiograms," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(12), pages 1948-1962, October.
    15. Eugene Garfield & A. I. Pudovkin & V. S. Istomin, 2003. "Why do we need algorithmic historiography?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 400-412, March.
    16. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.
    17. Shih-Chang Hung & John S. Liu & Louis Y. Y. Lu & Yu-Chiang Tseng, 2014. "Technological change in lithium iron phosphate battery: the key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 97-120, July.
    18. Mina, A. & Ramlogan, R. & Tampubolon, G. & Metcalfe, J.S., 2007. "Mapping evolutionary trajectories: Applications to the growth and transformation of medical knowledge," Research Policy, Elsevier, vol. 36(5), pages 789-806, June.
    19. Xiao, Yu & Lu, Louis Y.Y. & Liu, John S. & Zhou, Zhili, 2014. "Knowledge diffusion path analysis of data quality literature: A main path analysis," Journal of Informetrics, Elsevier, vol. 8(3), pages 594-605.
    20. Wullianallur Raghupathi & Sridhar Nerur, 2010. "The Intellectual Structure of Health and Medical Informatics," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 5(4), pages 20-34, October.
    21. Epicoco, Marianna & Oltra, Vanessa & Maïder Saint, Jean, 2014. "Knowledge dynamics and sources of eco-innovation: Mapping the Green Chemistry community," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 388-402.
    22. Hiran H. Lathabai & Susan George & Thara Prabhakaran & Manoj Changat, 2018. "An integrated approach to path analysis for weighted citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1871-1904, December.
    23. Yi-Ning Tu & Shu-Lan Hsu, 2016. "Constructing conceptual trajectory maps to trace the development of research fields," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(8), pages 2016-2031, August.
    24. John S. Liu & Chung-Huei Kuan, 2016. "A new approach for main path analysis: Decay in knowledge diffusion," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(2), pages 465-476, February.
    25. Chuang, Thomas C. & Liu, John S. & Lu, Louis Y.Y. & Lee, Yachi, 2014. "The main paths of medical tourism: From transplantation to beautification," Tourism Management, Elsevier, vol. 45(C), pages 49-58.
    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. Chung-Huei Kuan, 2023. "Does main path analysis prefer longer paths?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 841-851, January.
    2. Xiaorui Jiang & Junjun Liu, 2023. "Extracting the evolutionary backbone of scientific domains: The semantic main path network analysis approach based on citation context analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(5), pages 546-569, May.
    3. Martin Ho & Henry CW Price & Tim S Evans & Eoin O'Sullivan, 2023. "Order in Innovation," Papers 2302.13076, arXiv.org.
    4. Huang, Chen-Hao & Liu, John S. & Ho, Mei Hsiu-Ching & Chou, Tzu-Chuan, 2022. "Towards more convergent main paths: A relevance-based approach," Journal of Informetrics, Elsevier, vol. 16(3).
    5. Yu, Dejian & Yan, Zhaoping, 2023. "Main path analysis considering citation structure and content: Case studies in different domains," Journal of Informetrics, Elsevier, vol. 17(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. Chen, Liang & Xu, Shuo & Zhu, Lijun & Zhang, Jing & Xu, Haiyun & Yang, Guancan, 2022. "A semantic main path analysis method to identify multiple developmental trajectories," Journal of Informetrics, Elsevier, vol. 16(2).
    2. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.
    3. Flavia Filippin, 2021. "Do main paths reflect technological trajectories? Applying main path analysis to the semiconductor manufacturing industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6443-6477, August.
    4. Junmo Kim & Juneseuk Shin, 2018. "Mapping extended technological trajectories: integration of main path, derivative paths, and technology junctures," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1439-1459, September.
    5. Ichiro Watanabe & Soichiro Takagi, 2021. "Technological Trajectory Analysis of Patent Citation Networks: Examining the Technological Evolution of Computer Graphic Processing Systems," The Review of Socionetwork Strategies, Springer, vol. 15(1), pages 1-25, June.
    6. Ichiro Watanabe & Soichiro Takagi, 2022. "NK model-based analysis of technological trajectories: a study on the technological field of computer graphic processing systems," Evolutionary and Institutional Economics Review, Springer, vol. 19(1), pages 119-140, April.
    7. Yu, Dejian & Pan, Tianxing, 2021. "Tracing the main path of interdisciplinary research considering citation preference: A case from blockchain domain," Journal of Informetrics, Elsevier, vol. 15(2).
    8. Martin Ho & Henry CW Price & Tim S Evans & Eoin O'Sullivan, 2023. "Order in Innovation," Papers 2302.13076, arXiv.org.
    9. Huang, Chen-Hao & Liu, John S. & Ho, Mei Hsiu-Ching & Chou, Tzu-Chuan, 2022. "Towards more convergent main paths: A relevance-based approach," Journal of Informetrics, Elsevier, vol. 16(3).
    10. Xiaorui Jiang & Junjun Liu, 2023. "Extracting the evolutionary backbone of scientific domains: The semantic main path network analysis approach based on citation context analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(5), pages 546-569, May.
    11. Yu, Dejian & Sheng, Libo, 2021. "Influence difference main path analysis: Evidence from DNA and blockchain domain citation networks," Journal of Informetrics, Elsevier, vol. 15(4).
    12. Dejing Kong & Jianzhong Yang & Lingfeng Li, 2020. "Early identification of technological convergence in numerical control machine tool: a deep learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1983-2009, December.
    13. Alessandri, Enrico, 2023. "Identifying technological trajectories in the mining sector using patent citation networks," Resources Policy, Elsevier, vol. 80(C).
    14. Hiran H. Lathabai & Susan George & Thara Prabhakaran & Manoj Changat, 2018. "An integrated approach to path analysis for weighted citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1871-1904, December.
    15. Kuan, Chung-Huei & Chen, Dar-Zen & Huang, Mu-Hsuan, 2020. "The overlooked citations: Investigating the impact of ignoring citations to published patent applications," Journal of Informetrics, Elsevier, vol. 14(1).
    16. Abderahman Rejeb & Alireza Abdollahi & Karim Rejeb & Mohamed M. Mostafa, 2023. "Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2183-2209, June.
    17. Hwang, Seonho & Shin, Juneseuk, 2019. "Extending technological trajectories to latest technological changes by overcoming time lags," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 142-153.
    18. Chen, Kaihua & Zhang, Yi & Fu, Xiaolan, 2019. "International research collaboration: An emerging domain of innovation studies?," Research Policy, Elsevier, vol. 48(1), pages 149-168.
    19. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Liu, Ziqiang & Yuan, Guoting, 2020. "Topic-linked innovation paths in science and technology," Journal of Informetrics, Elsevier, vol. 14(2).
    20. Huenteler, Joern & Ossenbrink, Jan & Schmidt, Tobias S. & Hoffmann, Volker H., 2016. "How a product’s design hierarchy shapes the evolution of technological knowledge—Evidence from patent-citation networks in wind power," Research Policy, Elsevier, vol. 45(6), pages 1195-1217.

    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:16:y:2022:i:1:s1751157721001139. 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.