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Navigating the AI technology landscape from GitHub data

Author

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  • Choi, Jaemyoung
  • Lee, Sungsoo
  • Lee, Hakyeon

Abstract

As artificial intelligence (AI) is considered a pivotal technology determining competitiveness, understanding the current and future state of AI technology has become crucial. Conventional approaches to mapping the technology landscape have relied heavily on patent data, but patents cannot adequately capture the state of the art in rapidly changing technologies like AI, due to significant time lags from development to registration. Given that much of the AI technology is developed through open source projects on GitHub, the largest and most popular code host and social coding platform, GitHub emerges as a promising data source for navigating the AI technology landscape. This study aims to explore and predict the AI landscape based on GitHub data. We propose a new bibliometric-like measure, called library coupling, which leverages the unique aspect of code reuse in open source software development to capture the relationships between GitHub repositories. A total of 2879 AI-related repositories with Python-based libraries were collected from GitHub. An AI repository network is constructed based on library coupling relationships among these repositories. Using the attributed graph clustering technique, the AI repositories within the network are grouped into 20 AI technology clusters. Subsequently, we employ graph convolutional network-based link prediction to predict the changes in the AI technology landscape. The proposed GitHub-based technology landscaping approach can be effectively utilized to grasp the current state of rapidly evolving AI technologies and predict their future trends, thereby supporting informed decision making in national AI policy formulation and corporate AI strategy.

Suggested Citation

  • Choi, Jaemyoung & Lee, Sungsoo & Lee, Hakyeon, 2026. "Navigating the AI technology landscape from GitHub data," Technology in Society, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:teinso:v:84:y:2026:i:c:s0160791x25002805
    DOI: 10.1016/j.techsoc.2025.103090
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    1. Grimaldi, Michele & Cricelli, Livio & Di Giovanni, Martina & Rogo, Francesco, 2015. "The patent portfolio value analysis: A new framework to leverage patent information for strategic technology planning," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 286-302.
    2. Haefner, Naomi & Wincent, Joakim & Parida, Vinit & Gassmann, Oliver, 2021. "Artificial intelligence and innovation management: A review, framework, and research agenda✰," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    3. Huang, Lei & Ladikas, Miltos & Schippl, Jens & He, Guangxi & Hahn, Julia, 2023. "Knowledge mapping of an artificial intelligence application scenario: A bibliometric analysis of the basic research of data-driven autonomous vehicles," Technology in Society, Elsevier, vol. 75(C).
    4. Park, Mingyu & Geum, Youngjung, 2022. "Two-stage technology opportunity discovery for firm-level decision making: GCN-based link-prediction approach," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    5. Stefan Haefliger & Georg von Krogh & Sebastian Spaeth, 2008. "Code Reuse in Open Source Software," Management Science, INFORMS, vol. 54(1), pages 180-193, January.
    6. Chen, Ssu-Han & Huang, Mu-Hsuan & Chen, Dar-Zen, 2012. "Identifying and visualizing technology evolution: A case study of smart grid technology," Technological Forecasting and Social Change, Elsevier, vol. 79(6), pages 1099-1110.
    7. Bonino, Dario & Ciaramella, Alberto & Corno, Fulvio, 2010. "Review of the state-of-the-art in patent information and forthcoming evolutions in intelligent patent informatics," World Patent Information, Elsevier, vol. 32(1), pages 30-38, March.
    8. Erzurumlu, S. Sinan & Pachamanova, Dessislava, 2020. "Topic modeling and technology forecasting for assessing the commercial viability of healthcare innovations," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    9. Adamuthe, Amol C. & Thampi, Gopakumaran T., 2019. "Technology forecasting: A case study of computational technologies," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 181-189.
    10. Linares, Ian Marques Porto & De Paulo, Alex Fabianne & Porto, Geciane Silveira, 2019. "Patent-based network analysis to understand technological innovation pathways and trends," Technology in Society, Elsevier, vol. 59(C).
    11. Boyack, Kevin W. & Klavans, Richard, 2008. "Measuring science–technology interaction using rare inventor–author names," Journal of Informetrics, Elsevier, vol. 2(3), pages 173-182.
    12. Wang, Ning & Hagedoorn, John, 2014. "The lag structure of the relationship between patenting and internal R&D revisited," Research Policy, Elsevier, vol. 43(8), pages 1275-1285.
    13. Aharonson, Barak S. & Schilling, Melissa A., 2016. "Mapping the technological landscape: Measuring technology distance, technological footprints, and technology evolution," Research Policy, Elsevier, vol. 45(1), pages 81-96.
    14. S. Ravikumar & Ashutosh Agrahari & S. N. Singh, 2015. "Mapping the intellectual structure of scientometrics: a co-word analysis of the journal Scientometrics (2005–2010)," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 929-955, January.
    15. Murray, Fiona & Stern, Scott, 2007. "Do formal intellectual property rights hinder the free flow of scientific knowledge?: An empirical test of the anti-commons hypothesis," Journal of Economic Behavior & Organization, Elsevier, vol. 63(4), pages 648-687, August.
    16. Fiona E. Murray & Scott Stern, 2007. "Do Formal Intellectual Property Rights Hinder the Free Flow of Scientific Knowledge?: An Empirical Test of the Anti-Commons Hypothesis," NBER Chapters, in: Academic Science and Entrepreneurship: Dual Engines of Growth, National Bureau of Economic Research, Inc.
    17. Sung, Kiseo & Park, Kyu-Tae & Lee, Hakyeon, 2024. "Landscaping the digital twin technology: Patent-based networks and technology reference model," Technological Forecasting and Social Change, Elsevier, vol. 206(C).
    18. Fujii, Hidemichi & Managi, Shunsuke, 2018. "Trends and priority shifts in artificial intelligence technology invention: A global patent analysis," Economic Analysis and Policy, Elsevier, vol. 58(C), pages 60-69.
    19. Zhu, Chen & Motohashi, Kazuyuki, 2022. "Identifying the technology convergence using patent text information: A graph convolutional networks (GCN)-based approach," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    20. Chen, Xi & Mao, Jin & Li, Gang, 2024. "A co-citation approach to the analysis on the interaction between scientific and technological knowledge," Journal of Informetrics, Elsevier, vol. 18(3).
    21. Dotsika, Fefie & Watkins, Andrew, 2017. "Identifying potentially disruptive trends by means of keyword network analysis," Technological Forecasting and Social Change, Elsevier, vol. 119(C), pages 114-127.
    22. Nees Jan van Eck & Ludo Waltman, 2009. "How to normalize cooccurrence data? An analysis of some well‐known similarity measures," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(8), pages 1635-1651, August.
    23. Lü, Linyuan & Zhou, Tao, 2011. "Link prediction in complex networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1150-1170.
    24. Aleksandra Kuzior & Mariya Sira & Paulina Brożek, 2023. "Use of Artificial Intelligence in Terms of Open Innovation Process and Management," Sustainability, MDPI, vol. 15(9), pages 1-16, April.
    25. Bonaccorsi, Andrea & Rossi, Cristina, 2003. "Why Open Source software can succeed," Research Policy, Elsevier, vol. 32(7), pages 1243-1258, July.
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