Multilayer patent citation networks: A comprehensive analytical framework for studying explicit technological relationships
| Autor: | Kyle Higham, Martina Contisciani, Caterina De Bacco |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences Physics - Physics and Society Management of Technology and Innovation FOS: Physical sciences Computer Science - Social and Information Networks Physics and Society (physics.soc-ph) Business and International Management Applied Psychology |
| Zdroj: | Technological Forecasting and Social Change |
| DOI: | 10.48550/arxiv.2203.14479 |
| Popis: | The use of patent citation networks as research tools is becoming increasingly commonplace in the field of innovation studies. However, these networks rarely consider the contexts in which these citations are generated and are generally restricted to a single jurisdiction. Here, we propose and explore the use of a multilayer network framework that can naturally incorporate citation metadata and stretch across jurisdictions, allowing for a complete view of the global technological landscape that is accessible through patent data. Taking a conservative approach that links citation network layers through triadic patent families, we first observe that these layers contain complementary, rather than redundant, information about technological relationships. To probe the nature of this complementarity, we extract network communities from both the multilayer network and analogous single-layer networks, then directly compare their technological composition with established technological similarity networks. We find that while technologies are more splintered across communities in the multilayer case, the extracted communities match much more closely the established networks. We conclude that by capturing citation context, a multilayer representation of patent citation networks is, conceptually and empirically, better able to capture the significant nuance that exists in real technological relationships when compared to traditional, single-layer approaches. We suggest future avenues of research that take advantage of novel computational tools designed for use with multilayer networks. Comment: 44 pages, 5 figures, to be published in Technological Forecasting and Social Change |
| Databáze: | OpenAIRE |
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