Journals / Gazi Mühendislik Bilimleri Dergisi / 2026 / Volume: 11 Issue: 2

Global Trends and Collaboration Dynamics in Large Language Model Research: A Bibliometric Analysis

Mevlüt Uysal(GAZİ ÜNİVERSİTESİ)0000-0002-6934-4421
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Publication Date
2025-08-31
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The analysis reveals that the field has shown exponential growth since 2023, is shaped by the leadership of the USA and China, and is rapidly expanding beyond its theoretical core into applied areas like medicine and education

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Large Language Models (LLMs) have spearheaded a significant transformation in artificial intelligence, rapidly becoming a focal point of scientific research.
📊
Key Findings & Data:The research data comprises 10,321 articles that met the specified criteria, retrieved from the Web of Science (WoS) Core Collection database using the search term "large language model".
💡
Conclusion & Impact:The analysis reveals that the field has shown exponential growth since 2023, is shaped by the leadership of the USA and China, and is rapidly expanding beyond its theoretical core into applied areas like medicine and education
🔬Design:Modeling & Simulation
📍Scope:2023 Verileri
⚙️Variables:Large Language Models · Bibliometric Analysis · Science Mapping

Abstract

Large Language Models (LLMs) have spearheaded a significant transformation in artificial intelligence, rapidly becoming a focal point of scientific research. This study aims to comprehensively analyze the intellectual structure and temporal evolution of scientific publications on LLMs using bibliometric methods. The research data comprises 10,321 articles that met the specified criteria, retrieved from the Web of Science (WoS) Core Collection database using the search term "large language model". Performance analysis and science mapping techniques were applied using VOSviewer software for the data analysis and visualization. Within this scope, co-authorship, co-citation, and keyword co-occurrence analyses were conducted to identify the key actors, collaboration networks, intellectual foundations, and primary research topics in the field. The analysis reveals that the field has shown exponential growth since 2023, is shaped by the leadership of the USA and China, and is rapidly expanding beyond its theoretical core into applied areas like medicine and education

🔖

Cite This Article

Uysal, M. (2025). Global Trends and Collaboration Dynamics in Large Language Model Research: A Bibliometric Analysis. Gazi Mühendislik Bilimleri Dergisi, Volume: 11 Issue: 2. https://ajindex.com/articles/1397370

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References (38)

  1. H. Naveed, A. U. Khan, S. Qiu, M. Saqib, S. Anwar, M. Usman,. and A. Mian, "A comprehensive overview of large language models," ACM Transactions on Intelligent Systems and Technology, vol. 16, no. 5, pp. 1-72, Oct. 2025. doi: 10.1145/3744746
  2. W. X. Zhao, K. Zhou, J. Li, T. Tang, X. Wang, Y. Hou,. and J.-R. Wen, "A survey of large language models," arXiv preprint arXiv:2303.18223, 2023. doi: 10.48550/arXiv.2303.18223
  3. S. Han, M. Wang, J. Zhang, D. Li, and J. Duan, "A review of large language models: Fundamental architectures, key technological evolutions, interdisciplinary technologies integration, optimization and compression techniques, applications, and challenges," Electronics, vol. 13, no. 24, p. 5040, Dec. 2024. doi: 10.3390/electronics13245040
  4. L. Wu, Z. Zheng, Z. Qiu, H. Wang, H. Gu, T. Shen,. and E. Chen, "A survey on large language models for recommendation," World Wide Web, vol. 27, no. 5, Aug. 2024. doi: 10.1007/s11280-024-01291-2
  5. A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez,. and I. Polosukhin, "Attention is all you need," in Proc. of the 31st Int. Conf. on Neural Information Processing Systems (NeurIPS 2017), Dec. 4–9, 2017, Long Beach, CA, USA. Red Hook, NY: Curran Associates Inc., 2017, pp. 6000–6010
  6. J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, "BERT: Pre-training of deep bidirectional transformers for language understanding," arXiv preprint arXiv:1810.04805, 2018. doi: 10.48550/arXiv.1810.04805
  7. T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal,. and D. Amodei, "Language models are few-shot learners," in Proc. of NeurIPS 2020, Dec. 6–12, 2020, Virtual Conference. Red Hook, NY: Curran Associates Inc., 2020, pp. 1877–1901.
  8. G. Gencer and K. Gencer, "Large language models in healthcare: A bibliometric analysis and examination of research trends," Journal of Multidisciplinary Healthcare, vol. 18, pp. 223-238, Jan. 2025. doi: 10.2147/JMDH.S502351
  9. A. D. Damayanti, H. Gani, Z. Feng, H. Gani, S. Zuhriyah, N. Nurani,. and N. I. Wardani, "Bibliometric and content analysis of large language models research in software engineering: The potential and limitation in software engineering," International Journal of Advanced Computer Science and Applications (IJACSA), vol. 16, no. 4, 2025. doi: 10.14569/IJACSA.2025.0160436
  10. M. Oliński, K. Krukowski, and K. Sieciński, "Bibliometric overview of ChatGPT: New perspectives in social sciences," Publications, vol. 12, no. 1, 2024. doi: 10.3390/publications12010009
  11. C. Ziems, W. Held, O. Shaikh, J. Chen, Z. Zhang, and D. Yang, "Can large language models transform computational social science?" arXiv preprint arXiv:2305.03514, 2024. doi: 10.48550/arXiv.2305.03514
  12. L. Fan, L. Li, Z. Ma, S. Lee, H. Yu, and L. Hemphill, "A bibliometric review of large language models research from 2017 to 2023," ACM Transactions on Intelligent Systems and Technology, vol. 15, no. 5, pp. 1-25, Oct. 2024. doi: 10.1145/3664930
  13. Y. K. Dwivedi, N. Kshetri, L. Hughes, E. L. Slade, A. Jeyaraj, A. K. Kar,. and R. Wright, "Opinion paper: 'So what if ChatGPT wrote it?' Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy," International Journal of Information Management, vol. 71, Art 102642, 2023. doi: 10.1016/j.ijinfomgt.2023.102642
  14. R. Bommasani, D. A. Hudson, E. Adeli, R. Altman, S. Arora, S. von Arx,. and P. Liang, "On the opportunities and risks of foundation models," arXiv preprint arXiv:2108.07258, 2021. doi: 10.48550/arXiv.2108.07258
  15. M. Koo, "ChatGPT research: A bibliometric analysis based on the Web of Science from 2023 to June 2024," Knowledge, vol. 5, no. 1, 2025. doi: 10.3390/knowledge5010004
  16. I. F. S. Antunes and J. M. C. Veríssimo, "A bibliometric review and content analysis of research trends in sensory marketing," Cogent Business & Management, vol. 11, no. 1, 2024. doi: 10.1080/23311975.2024.2338879
  17. N. Donthu, S. Kumar, D. Mukherjee, N. Pandey, and W. M. Lim, "How to conduct a bibliometric analysis: An overview and guidelines," Journal of Business Research, vol. 133, pp. 285-296, 2021. doi: 10.1016/j.jbusres.2021.04.070
  18. I. Passas, "Bibliometric analysis: The main steps," Encyclopedia, vol. 4, no. 2, pp. 1014-1025, 2024. doi: 10.3390/encyclopedia4020065
  19. J. W. Ayers, A. Poliak, M. Dredze,. and others, "Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum," JAMA Internal Medicine, vol. 183, no. 6, pp. 589-596, 2023. doi: 10.1001/jamainternmed.2023.1838
  20. J. Liu, C. Wang, Z. Liu, M. Gao, Y. Xu, J. Chen,. and Y. Cheng, "A bibliometric analysis of generative AI in education: Current status and development," Asia Pacific Journal of Education, vol. 44, no. 1, pp. 156-175, 2024. doi: 10.1080/02188791.2024.2305170
  21. M. R. Zheltukhina, O. V. Sergeeva, A. R. Masalimova, R. L. Budkevich, N. N. Kosarenko,. and G. V. Nesterov, "A bibliometric analysis of publications on ChatGPT in education: Research patterns and topics," Online Journal of Communication and Media Technologies, vol. 14, no. 1, 2024. doi: 10.30935/ojcmt/14103
  22. B. Ersöz, Ş. Sağıroğlu, and H. İ. Bülbül, "Generative artificial intelligence opportunities and threats: Bibliometric analysis," in Proc. 9th Int. Conf. on Computer Science and Engineering (UBMK), Antalya, Türkiye, 2024, pp. 1-6. doi: 10.1109/UBMK63289.2024.10773519
  23. Y. Chang, X. Wang, J. Wang, Y. Wu, L. Yang, K. Zhu,. and X. Xie, "A survey on evaluation of large language models," ACM Transactions on Intelligent Systems and Technology, vol. 15, no. 3, pp. 1-45, Jun. 2024. doi: 10.1145/3641289
  24. A. Martín-Martín, E. Orduna-Malea, M. Thelwall, and E. D. López-Cózar, "Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories," Journal of Informetrics, vol. 12, no. 4, pp. 1160-1177, 2018. doi: 10.1016/j.joi.2018.09.002
  25. N. J. van Eck and L. Waltman, "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, vol. 84, pp. 523-538, 2010. doi: 10.1007/s11192-009-0146-3
  26. A. Kirby, "Exploratory bibliometrics: Using VOSviewer as a preliminary research tool," Publications, vol. 11, no. 1, 2023. doi: 10.3390/publications11010010
  27. H. Naveed, A. U. Khan, S. Qiu, M. Saqib, S. Anwar, M. Usman,. and A. Mian, "A comprehensive overview of large language models," ACM Transactions on Intelligent Systems and Technology, vol. 16, no. 5, pp. 1-72, Oct. 2025. doi: 10.1145/3744746
  28. W. X. Zhao, K. Zhou, J. Li, T. Tang, X. Wang, Y. Hou,. and J.-R. Wen, "A survey of large language models," arXiv preprint arXiv:2303.18223, 2023. doi: 10.48550/arXiv.2303.18223
  29. L. Wu, Z. Zheng, Z. Qiu, H. Wang, H. Gu, T. Shen,. and E. Chen, "A survey on large language models for recommendation," World Wide Web, vol. 27, no. 5, Aug. 2024. doi: 10.1007/s11280-024-01291-2
  30. A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez,. and I. Polosukhin, "Attention is all you need," in Proc. of the 31st Int. Conf. on Neural Information Processing Systems (NeurIPS 2017), Dec. 4–9, 2017, Long Beach, CA, USA. Red Hook, NY: Curran Associates Inc., 2017, pp. 6000–6010
  31. T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal,. and D. Amodei, "Language models are few-shot learners," in Proc. of NeurIPS 2020, Dec. 6–12, 2020, Virtual Conference. Red Hook, NY: Curran Associates Inc., 2020, pp. 1877–1901.
  32. A. D. Damayanti, H. Gani, Z. Feng, H. Gani, S. Zuhriyah, N. Nurani,. and N. I. Wardani, "Bibliometric and content analysis of large language models research in software engineering: The potential and limitation in software engineering," International Journal of Advanced Computer Science and Applications (IJACSA), vol. 16, no. 4, 2025. doi: 10.14569/IJACSA.2025.0160436
  33. Y. K. Dwivedi, N. Kshetri, L. Hughes, E. L. Slade, A. Jeyaraj, A. K. Kar,. and R. Wright, "Opinion paper: 'So what if ChatGPT wrote it?' Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy," International Journal of Information Management, vol. 71, Art 102642, 2023. doi: 10.1016/j.ijinfomgt.2023.102642
  34. R. Bommasani, D. A. Hudson, E. Adeli, R. Altman, S. Arora, S. von Arx,. and P. Liang, "On the opportunities and risks of foundation models," arXiv preprint arXiv:2108.07258, 2021. doi: 10.48550/arXiv.2108.07258
  35. J. W. Ayers, A. Poliak, M. Dredze,. and others, "Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum," JAMA Internal Medicine, vol. 183, no. 6, pp. 589-596, 2023. doi: 10.1001/jamainternmed.2023.1838
  36. J. Liu, C. Wang, Z. Liu, M. Gao, Y. Xu, J. Chen,. and Y. Cheng, "A bibliometric analysis of generative AI in education: Current status and development," Asia Pacific Journal of Education, vol. 44, no. 1, pp. 156-175, 2024. doi: 10.1080/02188791.2024.2305170
  37. M. R. Zheltukhina, O. V. Sergeeva, A. R. Masalimova, R. L. Budkevich, N. N. Kosarenko,. and G. V. Nesterov, "A bibliometric analysis of publications on ChatGPT in education: Research patterns and topics," Online Journal of Communication and Media Technologies, vol. 14, no. 1, 2024. doi: 10.30935/ojcmt/14103
  38. Y. Chang, X. Wang, J. Wang, Y. Wu, L. Yang, K. Zhu,. and X. Xie, "A survey on evaluation of large language models," ACM Transactions on Intelligent Systems and Technology, vol. 15, no. 3, pp. 1-45, Jun. 2024. doi: 10.1145/3641289