Bibliometric Analysis of Artificial Intelligence Literacy Research Status Based on Clustering

With the rapid development of artificial intelligence (AI) techniques, people more and more rely on generative AI (GenAI) to fulfill a variety of tasks. Thus, the popularity of AI is arousing people’s attention to AI literacy. However, few current existing studies or scientific methods can systematically summarize AI literacy systematically. Therefore, aiming to use library statistic-based clustering techniques to analyze AI literacy, this paper uses clustering to perform summarizing based on library statistic analysis rules. Subsequently, bibliometric analysis and VOSviewer visualization tools are used to conduct a comprehensive review of the academic literature in the field of AI literacy. With better parameters and rules, the summary proposed in this paper can outperform the baseline clustering models. Experimental results show that better summaries can be obtained and visualized by using our proposed method. Additionally, this study points out the limitations of the research and provides direction for improvement in subsequent studies.