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Filippi-Mazzola_2024_OUP_Royal Stat Soc C_A stochastic gradient
Journal article

A stochastic gradient relational event additive model for modelling US patent citations from 1976 to 2022

  • Filippi-Mazzola, Edoardo ORCID Institute of Computing (CI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • Wit, Ernst C. ORCID Institute of Computing (CI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • 2024
Published in:
  • Journal of the royal statistical society series C: applied statistics. - 2024, vol. 73, no. 4, p. 1008-1024
B-splines
Citation networks
Patent analysis
rRelational event models
Stochastic gradient descent
English Until 2022, the US patent citation network contained almost 10 million patents and over 100 million citations, presenting a challenge in analysing such expansive, intricate networks. To overcome limitations in analysing this complex citation network, we propose a stochastic gradient relational event additive model (STREAM) that models the citation relationships between patents as time events. While the structure of this model relies on the relational event model, STREAM offers a more comprehensive interpretation by modelling the effect of each predictor non-linearly. Overall, our model identifies key factors driving patent citations and reveals insights in the citation process.
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Language
  • English
Classification
Mathematics
License
CC BY
Open access status
hybrid
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Persistent URL
https://n2t.net/ark:/12658/srd1330230
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