IDEAS home Printed from https://ideas.repec.org/a/bla/jamist/v59y2008i12p1948-1962.html
   My bibliography  Save this article

Main‐path analysis and path‐dependent transitions in HistCite™‐based historiograms

Author

Listed:
  • Diana Lucio‐Arias
  • Loet Leydesdorff

Abstract

With the program HistCite™ it is possible to generate and visualize the most relevant papers in a set of documents retrieved from the Science Citation Index. Historical reconstructions of scientific developments can be represented chronologically as developments in networks of citation relations extracted from scientific literature. This study aims to go beyond the historical reconstruction of scientific knowledge, enriching the output of HistCite™ with algorithms from social‐network analysis and information theory. Using main‐path analysis, it is possible to highlight the structural backbone in the development of a scientific field. The expected information value of the message can be used to indicate whether change in the distribution (of citations) has occurred to such an extent that a path‐dependency is generated. This provides us with a measure of evolutionary change between subsequent documents. The “forgetting and rewriting” of historically prior events at the research front can thus be indicated. These three methods—HistCite, main path and path dependent transitions—are applied to a set of documents related to fullerenes and the fullerene‐like structures known as nanotubes.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:jamist:v:59:y:2008:i:12:p:1948-1962
    DOI: 10.1002/asi.20903
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asi.20903
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asi.20903?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Yi & Huang, Ying & Porter, Alan L. & Zhang, Guangquan & Lu, Jie, 2019. "Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 795-807.
    2. Niccol? Comerio & Patrizia Tettamanzi, 2019. "Systematic literature network analysis in accounting: A first application on integrated reporting research," FINANCIAL REPORTING, FrancoAngeli Editore, vol. 2019(2), pages 73-95.
    3. Kosztyán, Zsolt T. & Csizmadia, Tibor & Katona, Attila I., 2021. "SIMILAR – Systematic iterative multilayer literature review method," Journal of Informetrics, Elsevier, vol. 15(1).
    4. Tam Eunice Wai-si & Yip Joanne & Lo Kwan Yu & Yick Kit Lun & Fang Christian & Ng Sun Pui, 2020. "De Quervain's Tenosynovitis- A Systematic and Citation Network Analysis Review," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 24(5), pages 18674-18684, January.
    5. 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.
    6. 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.
    7. Martin Ho & Henry CW Price & Tim S Evans & Eoin O'Sullivan, 2023. "Order in Innovation," Papers 2302.13076, arXiv.org.
    8. 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).
    9. Geoffrey M. Hodgson & Juha-Antti Lamberg, 2018. "The past and future of evolutionary economics: some reflections based on new bibliometric evidence," Evolutionary and Institutional Economics Review, Springer, vol. 15(1), pages 167-187, June.
    10. 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.
    11. Ben Zhang & Lei Ma & Zheng Liu, 2020. "Literature Trend Identification of Sustainable Technology Innovation: A Bibliometric Study Based on Co-Citation and Main Path Analysis," Sustainability, MDPI, vol. 12(20), pages 1-20, October.
    12. 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.
    13. Fang Han & Sejun Yoon & Nagarajan Raghavan & Hyunseok Park, 2022. "Investigating Company’s Technical Development Directions Based on Internal Knowledge Inheritance and Inventor Capabilities: The Case of Samsung Electronics," Sustainability, MDPI, vol. 14(5), pages 1-19, March.
    14. Shen, Neng & Deng, Rumeng & Liao, Haolan & Shevchuk, Oleksandr, 2020. "Mapping renewable energy subsidy policy research published from 1997 to 2018: A scientometric review," Utilities Policy, Elsevier, vol. 64(C).
    15. Hansin Bilgili & Jonathan L. Johnson & Tsvetomira V. Bilgili & Alan E. Ellstrand, 2022. "Research on social relationships and processes governing the behaviors of members of the corporate elite: a review and bibliometric analysis," Review of Managerial Science, Springer, vol. 16(8), pages 2285-2339, November.
    16. Song-Chia Hsu & Kai-Ying Chen & Chih-Ping Lin & Wei-Hao Su, 2022. "Knowledge Development Trajectories of Crime Prevention Domain: An Academic Study Based on Citation and Main Path Analysis," IJERPH, MDPI, vol. 19(17), pages 1-20, August.

    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:bla:jamist:v:59:y:2008:i:12:p:1948-1962. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    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.