Comprehensive Bibliometric Literature Review of Chatbot Research: Trends, Frameworks, and Emerging Applications

This study aims to conduct a comprehensive bibliometric literature review of chatbot research by examining key trends, frameworks, and influential applications across various domains. It seeks to map the evolution of chatbot technologies, identify influential works, and analyze how the research focus has shifted over time, particularly towards AI-driven chatbot frameworks. An expanded dataset was compiled from the Scopus database, and bibliometric analyses were conducted using n-gram reference analysis, network mapping, and temporal trend visualization. The analysis was performed using R Studio with Biblioshiny, allowing for the identification of thematic clusters and the progression from rule-based to advanced retrieval and generative language model paradigms in chatbot research. Chatbot research has grown significantly from 2020 to 2024, with rising publication volumes and increased global collaboration, led by contributions from the USA, China, and emerging regions, such as Southeast Asia. Thematic analysis highlights a shift from foundational AI and NLP technologies to specialized applications such as mental health chatbots and e-commerce systems, emphasizing practical and user-centered solutions. Advances in chatbot architectures, including generative AI, have demonstrated the field's interdisciplinary nature and trajectory towards sophisticated, context-aware conversational systems. The analysis primarily used data from Scopus, which may limit the breadth of the included research. Future studies are encouraged to integrate data from other sources, such as the Web of Science (WoS) and PubMed, for a more comprehensive understanding of the field.

@article{Harahap2025,
  title     = {Comprehensive Bibliometric Literature Review of Chatbot Research: Trends, Frameworks, and Emerging Applications},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {1},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Nazruddin Safaat Harahap and Aslina Saad and Nor Hasbiah Ubaidullah},
  doi       = {10.14569/IJACSA.2025.0160185},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160185}
}