Bibliometric Analysis of Scientific Trends at the Intersection of Artificial Intelligence, Cloud Computing, and Network Technologies

This study aims to bibliometrically analyze the literature on artificial intelligence, Cloud computing, and network technologies, structured around the keywords 'artificial intelligence , cloud computing, network'. In a search conducted on the Web of Science Core Collection database on November 24, 2025; a dataset consisting of 1,546 documents (including articles, early access papers, and book chapters) published between 2016 and 2026 was obtained by taking the term 'artificial intelligence' as a basis and subsequently narrowing it down with the concepts of 'cloud computing' and 'network'.The obtained records were imported into VOSviewer 1.6.20 software for analysis. The study examined article and citation trends by publication year, source types, bibliographic coupling at the country and institutional levels, author collaboration networks, document-based citation relationships, and co-occurrence maps of author keywords. The findings indicate a dramatic increase in the number of publications, particularly in the post-2020 period; the field reached a peak in 2025 with 295 articles, suggesting that the research volume in this area is rapidly transitioning into a maturation phase. It was determined that research is primarily concentrated in the categories of Computer Science, Electrical Engineering, and Telecommunications, with a significant expansion into disciplines such as security, big data, IoT, and edge computing. Keyword cooccurrence analysis revealed strong clusters of terms including 'artificial intelligence', 'cloud computing', 'edge computing', 'deep learning', 'resource management', '5G networks', and 'cybersecurity'; demonstrating that the literature is fundamentally structured around themes of distributed architectures, task allocation/optimization processes, intelligent systems, and security. Network analyses at the country and author levels indicate that countries such as China, the USA, the UK, and India, along with researchers like Chen M., Gill S.S., Chen X., Li Y., and Leung V.C.M., occupy a central position in the field. The increase in multidisciplinary research within the dataset suggests that studies conducted at the intersection of AI–Cloud–Network are becoming increasingly collaborative and integrated in nature. The findings reveal that the integration of artificial intelligence, cloud computing, and networks is rapidly evolving in both conceptual and applied dimensions; demonstrating that the scientific trends in the field are maturing within the framework of big data, edge computing, resource management, and secure communication technolohies.