Academic Journal
Unraveling technology diffusion through dynamic network and multi-dimensional mechanism analysis: evidence from natural language processing.
| Τίτλος: | Unraveling technology diffusion through dynamic network and multi-dimensional mechanism analysis: evidence from natural language processing. |
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| Συγγραφείς: | Yang Junhao, Xu Haiyun, Robin, Haunschild, Li Shuying, Liu Chunjiang, Yu XueLi |
| Πηγή: | Information Research; 2026 Special Issue, Vol. 31, p776-800, 25p |
| Θεματικοί όροι: | Natural language processing, Time-varying networks, Social network analysis, Technology transfer, Patent databases |
| Περίληψη: | Introduction. Understanding factors influencing technology diffusion is vital for optimizing technological environments and fostering innovation. Existing studies often overlook temporal dependence and lack multidimensional mechanism analysis. This study addresses these gaps by introducing a dynamic network perspective to analyze technology diffusion. Method. We developed a framework that integrates topic extraction with dynamic relationship modeling. Using patent data, BERTopic was applied to identify technological topics and construct cross time-slice diffusion networks. Social network analysis captured evolutionary patterns, while the temporal exponential random graph model (TERGM) jointly examined endogenous network structures, actor - relation effects, and exogenous factors. Analysis. The natural language processing field was selected as a case study. Diffusion dynamics and mechanism factors were investigated through quantitative modeling of temporal networks. Results. The network has become more cohesive yet decentralized. Core nodes remain but their bridging role weakens. Reciprocity strongly promotes diffusion. Topic influence, novelty, and knowledge quality positively drive relationship formation, while knowledge breadth and depth affect only the sender effect. Conclusions. This study integrates dynamic networks with multidimensional mechanism analysis, bridging gaps in temporal evolution and mechanism exploration, and providing a reusable framework and empirical reference for technology diffusion research. [ABSTRACT FROM AUTHOR] |
| Copyright of Information Research is the property of University of Boras and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Unraveling technology diffusion through dynamic network and multi-dimensional mechanism analysis: evidence from natural language processing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yang+Junhao%22">Yang Junhao</searchLink><br /><searchLink fieldCode="AR" term="%22Xu+Haiyun%22">Xu Haiyun</searchLink><br /><searchLink fieldCode="AR" term="%22Robin%2C+Haunschild%22">Robin, Haunschild</searchLink><br /><searchLink fieldCode="AR" term="%22Li+Shuying%22">Li Shuying</searchLink><br /><searchLink fieldCode="AR" term="%22Liu+Chunjiang%22">Liu Chunjiang</searchLink><br /><searchLink fieldCode="AR" term="%22Yu+XueLi%22">Yu XueLi</searchLink> – Name: TitleSource Label: Source Group: Src Data: Information Research; 2026 Special Issue, Vol. 31, p776-800, 25p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Natural+language+processing%22">Natural language processing</searchLink><br /><searchLink fieldCode="DE" term="%22Time-varying+networks%22">Time-varying networks</searchLink><br /><searchLink fieldCode="DE" term="%22Social+network+analysis%22">Social network analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+transfer%22">Technology transfer</searchLink><br /><searchLink fieldCode="DE" term="%22Patent+databases%22">Patent databases</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Introduction. Understanding factors influencing technology diffusion is vital for optimizing technological environments and fostering innovation. Existing studies often overlook temporal dependence and lack multidimensional mechanism analysis. This study addresses these gaps by introducing a dynamic network perspective to analyze technology diffusion. Method. We developed a framework that integrates topic extraction with dynamic relationship modeling. Using patent data, BERTopic was applied to identify technological topics and construct cross time-slice diffusion networks. Social network analysis captured evolutionary patterns, while the temporal exponential random graph model (TERGM) jointly examined endogenous network structures, actor - relation effects, and exogenous factors. Analysis. The natural language processing field was selected as a case study. Diffusion dynamics and mechanism factors were investigated through quantitative modeling of temporal networks. Results. The network has become more cohesive yet decentralized. Core nodes remain but their bridging role weakens. Reciprocity strongly promotes diffusion. Topic influence, novelty, and knowledge quality positively drive relationship formation, while knowledge breadth and depth affect only the sender effect. Conclusions. This study integrates dynamic networks with multidimensional mechanism analysis, bridging gaps in temporal evolution and mechanism exploration, and providing a reusable framework and empirical reference for technology diffusion research. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Information Research is the property of University of Boras and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.47989/ir31iConf64140 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 25 StartPage: 776 Subjects: – SubjectFull: Natural language processing Type: general – SubjectFull: Time-varying networks Type: general – SubjectFull: Social network analysis Type: general – SubjectFull: Technology transfer Type: general – SubjectFull: Patent databases Type: general Titles: – TitleFull: Unraveling technology diffusion through dynamic network and multi-dimensional mechanism analysis: evidence from natural language processing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yang Junhao – PersonEntity: Name: NameFull: Xu Haiyun – PersonEntity: Name: NameFull: Robin, Haunschild – PersonEntity: Name: NameFull: Li Shuying – PersonEntity: Name: NameFull: Liu Chunjiang – PersonEntity: Name: NameFull: Yu XueLi IsPartOfRelationships: – BibEntity: Dates: – D: 02 M: 01 Text: 2026 Special Issue Type: published Y: 2026 Identifiers: – Type: issn-print Value: 13681613 Numbering: – Type: volume Value: 31 Titles: – TitleFull: Information Research Type: main |
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