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A structural analysis of the patent citation network by the k-shell decomposition method

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  • Angelou, Konstantinos
  • Maragakis, Michael
  • Argyrakis, Panos

Abstract

We study the patent citation network by means of structural analysis. Specifically, we use the k-shell decomposition method to reveal hidden structural properties. We aim to identify the characteristics of the most important nodes in the network, as well as extract any existing patterns in the connectedness of these nodes. We examine properties of the nodes such as the geographic origin and the thematic area they belong. Results yield unexpected information on which are the most important nodes in the network, and how these nodes are geographically and thematically distributed.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:521:y:2019:i:c:p:476-483
    DOI: 10.1016/j.physa.2019.01.063
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    References listed on IDEAS

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    Cited by:

    1. Liu, Weiwei & Song, Yifan & Bi, Kexin, 2021. "Exploring the patent collaboration network of China's wind energy industry: A study based on patent data from CNIPA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    2. 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).
    3. Cao, Huiying & Gao, Chao & Wang, Zhen, 2023. "Ranking academic institutions by means of institution–publication networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).

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