Human-chatbot interaction studies through the lens of bibliometric analysis

Jiahao Chen, Fu Guo (Corresponding author), Zenggen Ren, Xueshuang Wang, Jaap Ham

Research output: Contribution to journalReview articlepeer-review


Since chatbots have been integrated into people’s lives from various industries, human-chatbot interaction has begun to attract widespread attention in academia. Still, contributions to the systematic mapping of this field are lacking. This paper is the first to present a systematic review of human-chatbot interaction research using bibliometric analysis. A total of 3013 publications (from the year 2000 to 2022) from Web of Science database were analysed to uncover the current status and research trend in human-chatbot interaction domain. The analysis focused on temporal and geographical distribution of these publications and identified the most influential publication outlets, institutes, articles, and authors. Additionally, keyword co-occurrence analysis and temporal distribution of keywords showed that primary topics in human-chatbot interaction mainly concentrate on techniques and methods in chatbot systems design, extensive applications in various fields, user experience and emotional expression, humanizing features design, and perceived privacy risk and ethics. Finally, this paper sheds light on a comprehensive understanding of human-chatbot interaction research and provides directions for future research in this field.

Original languageEnglish
JournalUniversal Access in the Information Society
Issue numberX
Early online date27 Oct 2023
Publication statusE-pub ahead of print - 27 Oct 2023


This work was supported by the National Natural Science Foundation of China (Grant No. 72071035).

FundersFunder number
National Natural Science Foundation of China72071035


    • Artificial Intelligence
    • Bibliometric analysis
    • Chatbots
    • Conversational agents
    • Human-chatbot interaction


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