IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v541y2020ics0378437119318813.html
   My bibliography  Save this article

A hybrid model for the patent citation network structure

Author

Listed:
  • Angelou, Konstantinos
  • Maragakis, Michael
  • Kosmidis, Kosmas
  • Argyrakis, Panos

Abstract

Percolation theory on the patent citation network is studied and the percolation threshold points are identified. The results show that there is a significant change of the threshold throughout our dataset years, implying changes in the formation process of the patent citation network. There is a first shift at around 2001, and a very delayed transition point after 2008. Giant component formation in such networks is an indication of the existence of inter-disciplinary patents. In order to explain the changes observed, a hybrid model for creating networks is suggested here. The model is based on a combination of random networks and preferential attachment. It is also compared with results from the well-known configuration model. The hybrid model fits better the data of the patent citation network, rather than a single scale-free or a single Erdős–Rényi network, and explains the increase in preferential attachment in later years. Both the degree distribution and the results of the analysis through percolation theory agree well with real data. This enables the formation of a plausible explanation for the structural changes of the patent citation network’s evolution.

Suggested Citation

  • Angelou, Konstantinos & Maragakis, Michael & Kosmidis, Kosmas & Argyrakis, Panos, 2020. "A hybrid model for the patent citation network structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    • Handle: RePEc:eee:phsmap:v:541:y:2020:i:c:s0378437119318813
    DOI: 10.1016/j.physa.2019.123363
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119318813
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.123363?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. Lingfei Wu & Dashun Wang & James A. Evans, 2019. "Large teams develop and small teams disrupt science and technology," Nature, Nature, vol. 566(7744), pages 378-382, February.
    2. Angelou, Konstantinos & Maragakis, Michael & Argyrakis, Panos, 2019. "A structural analysis of the patent citation network by the k-shell decomposition method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 476-483.
    3. Criscuolo, Paola & Verspagen, Bart, 2008. "Does it matter where patent citations come from? Inventor vs. examiner citations in European patents," Research Policy, Elsevier, vol. 37(10), pages 1892-1908, December.
    4. Gergely Palla & Albert-László Barabási & Tamás Vicsek, 2007. "Quantifying social group evolution," Nature, Nature, vol. 446(7136), pages 664-667, April.
    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. Lv, Yuqian & Zhou, Bo & Wang, Jinhuan & Xuan, Qi, 2024. "Targeted k-node collapse problem: Towards understanding the robustness of local k-core structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    2. Agrawal, Smita & Patel, Atul, 2021. "SAG Cluster: An unsupervised graph clustering based on collaborative similarity for community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    3. Angelou, K. & Maragakis, M. & Kosmidis, K. & Argyrakis, P., 2021. "The evolution of triangular research and innovation collaborations in the European area," Journal of Informetrics, Elsevier, vol. 15(3).

    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. Liu, Meijun & Jaiswal, Ajay & Bu, Yi & Min, Chao & Yang, Sijie & Liu, Zhibo & Acuña, Daniel & Ding, Ying, 2022. "Team formation and team impact: The balance between team freshness and repeat collaboration," Journal of Informetrics, Elsevier, vol. 16(4).
    2. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.
    3. Higham, Kyle & Contisciani, Martina & De Bacco, Caterina, 2022. "Multilayer patent citation networks: A comprehensive analytical framework for studying explicit technological relationships," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    4. Tian, Yunpei & Li, Gang & Mao, Jin, 2023. "Predicting the evolution of scientific communities by interpretable machine learning approaches," Journal of Informetrics, Elsevier, vol. 17(2).
    5. Ma, Guoshuai & Yuhua, Qian & Zhang, Yayu & Yan, Hongren & Cheng, Honghong & Hu, Zhiguo, 2022. "The recognition of kernel research team," Journal of Informetrics, Elsevier, vol. 16(4).
    6. Seokbeom Kwon & Jan Youtie & Alan Porter & Nils Newman, 2024. "How does regulatory uncertainty shape the innovation process? Evidence from the case of nanomedicine," The Journal of Technology Transfer, Springer, vol. 49(1), pages 262-302, February.
    7. Hoekman, Jarno & Rake, Bastian, 2024. "Geography of authorship: How geography shapes authorship attribution in big team science," Research Policy, Elsevier, vol. 53(2).
    8. Tetsuo Wada, 2018. "The choice of examiner patent citations for refusals: evidence from the trilateral offices," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 825-843, November.
    9. Battke, Benedikt & Schmidt, Tobias S. & Stollenwerk, Stephan & Hoffmann, Volker H., 2016. "Internal or external spillovers—Which kind of knowledge is more likely to flow within or across technologies," Research Policy, Elsevier, vol. 45(1), pages 27-41.
    10. Emanuele Bacchiocchi & Fabio Montobbio, 2010. "International Knowledge Diffusion and Home‐bias Effect: Do USPTO and EPO Patent Citations Tell the Same Story?," Scandinavian Journal of Economics, Wiley Blackwell, vol. 112(3), pages 441-470, September.
    11. Rajneesh Narula & Grazia D. Santangelo, 2007. "Location and R&D Alliances in the European ICT Industry," DRUID Working Papers 07-05, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
    12. Krzysztof Klincewicz & Szymon Szumiał, 2022. "Successful patenting—not only how, but with whom: the importance of patent attorneys," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5111-5137, September.
    13. Sungho Son & Nam-Wook Cho, 2020. "Technology Fusion Characteristics in the Solar Photovoltaic Industry of South Korea: A Patent Network Analysis Using IPC Co-Occurrence," Sustainability, MDPI, vol. 12(21), pages 1-19, October.
    14. Jan Fagerberg & Maryann Feldman & Martin Srholec, 2011. "Technological Dynamics and Social Capability: Comparing U.S. States and European Nations," Working Papers on Innovation Studies 20111114, Centre for Technology, Innovation and Culture, University of Oslo.
    15. Dirk Czarnitzki & Katrin Hussinger & Bart Leten, 2020. "How Valuable are Patent Blocking Strategies?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 56(3), pages 409-434, May.
    16. Inchae Park & Yujin Jeong & Byungun Yoon, 2017. "Analyzing the value of technology based on the differences of patent citations between applicants and examiners," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 665-691, May.
    17. Michele Pezzoni & Fabiana Visentin, 2024. "Gender bias in team formation: the case of the European Science Foundation’s grants," Science and Public Policy, Oxford University Press, vol. 51(2), pages 247-260.
    18. Cinzia Daraio & Simone Di Leo & Loet Leydesdorff, 2022. "Using the Leiden Rankings as a Heuristics: Evidence from Italian universities in the European landscape," LEM Papers Series 2022/08, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    19. Duede, Eamon & Teplitskiy, Misha & Lakhani, Karim & Evans, James, 2024. "Being together in place as a catalyst for scientific advance," Research Policy, Elsevier, vol. 53(2).
    20. Li, Heyang & Wu, Meijun & Wang, Yougui & Zeng, An, 2022. "Bibliographic coupling networks reveal the advantage of diversification in scientific projects," Journal of Informetrics, Elsevier, vol. 16(3).

    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:phsmap:v:541:y:2020:i:c:s0378437119318813. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.