Deciphering Research Trends in AI-Chatbots: A Social Science Perspective Using Bibliometric and Network Visualization Analysis

This is the authors' abstract. We don't add key points for this paper.

Chatbots have emerged as a transformative technology across various sectors, necessitating a comprehensive analysis of the directions of the intellectual and social landscape. This study addresses the current state of the intellectual and social structure of AI chatbots in social science over the past three decades by employing a systematic approach using the Scopus database, yielding 1358 articles. The current state of research and future directions of this field were examined using bibliographic coupling and keyword analysis. Data visualization and analysis were also carried out using RStudio in conjunction with VOS viewer and MS Excel. The findings indicate that research on chatbots has evolved over the past three decades. Utilizing keyword analysis, six distinct clusters of research were identified. The co-authorship network and bibliographic coupling analysis suggest that the USA and China, two countries with very different economies, histories, cultures, and locations have the highest number of cross-national chatbot study collaborations.