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Socio-technical Transitions in the AI Innovation Ecosystem: A Multi-layer Network Analysis of News and Academic Discourse

In: Technology Management for Intelligent, Open and Responsible Organizations and Ecosystems

Author

Listed:
  • Yeokyung Hwang

    (Seoul National University)

  • Junseok Hwang

    (Seoul National University)

  • Junmin Lee

    (Pusan National University)

Abstract

As artificial intelligence (AI) rapidly transforms multiple sectors, significant gaps persist between technological advancement and social understanding. This study examines the socio-technical transition dynamics of AI through multi-layer network analysis of news articles and academic papers from 1980–2023. By analysing approximately 800,000 news articles and over 12 million academic papers, we reveal distinct evolutionary patterns between technological and social domains. Academic networks demonstrated stable, incremental knowledge development, while news networks exhibited dynamic reconfiguration reflecting rapid societal adaptations. Our findings highlight the complementary functions within the AI socio-technical system, showing that academic stability ensures sustained technological advancement, while media flexibility enables societal adaptation.

Suggested Citation

  • Yeokyung Hwang & Junseok Hwang & Junmin Lee, 2026. "Socio-technical Transitions in the AI Innovation Ecosystem: A Multi-layer Network Analysis of News and Academic Discourse," Springer Proceedings in Business and Economics, in: Fabiano Armellini & Syrine Njah & Elaine Mosconi & Breno Nunes (ed.), Technology Management for Intelligent, Open and Responsible Organizations and Ecosystems, pages 21-28, Springer.
    • Handle: RePEc:spr:prbchp:978-3-032-23282-3_3
    DOI: 10.1007/978-3-032-23282-3_3
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