A stochastic gradient relational event additive model for modelling US patent citations from 1976 to 2022
Informazioni aggiuntive
Autori
Filippi-Mazzola E. G.,
Wit E. J.
Tipo
Articolo pubblicato in rivista scientifica
Anno
2024
Lingua
Inglese
Sommario
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.
Parole chiave
B-splines, Citation networks, Patent analysis, rRelational event models, Stochastic gradient descent
Periodico
Journal of the royal statistical society series C: applied statistics
Volume
73
Numero ( Mese )
4
Pagine (o numero dell’articolo)
1008-1024
Diffusione
Licenza
CC BY
Visibilità
Pubblico
Status open access
Hybrid
