The state of metaverse research: a bibliometric visual analysis based on CiteSpace

IF 8.6 2区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

Journal of Big Data Pub Date : 2024-01-10 DOI:10.1186/s40537-024-00877-x

Huike Li, Bo Li

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Abstract

Objective

To understand the current status of research in the field of metaverse, and to analyze the research progress and evolutionary trends in this field.

Methods

Based on the bibliometric analysis, a total of 921 papers were obtained by searching the Web of science core database for the keyword "metaverse". CiteSpace was used to visualize and analyze the current status and trends of metaverse research in China.

Results

Ireland is currently the country with the highest research impact. China is currently the country with the largest number of publications in this field, but the impact of the research is insufficient. The current research in the highly cited literature focuses on technical and history reviews of the metaverse as well as its development in the field of education. Artificial Intelligence and utaut2 are the underlying clusters of cited literature in this research area. Several research hotspots have been formed, such as virtual reality, augmented reality, mixed reality, digital twins and artificial intelligence.

Conclusion

The current research on metaverse in various fields is basically in its infancy, but has a great potential for future development and will gradually penetrate into many different directions with many challenges.

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元宇宙研究现状：基于 CiteSpace 的文献计量视觉分析

方法基于文献计量学分析，在Web of science核心数据库中以 "metaverse "为关键词进行检索，共获得921篇论文。结果爱尔兰是目前研究影响最大的国家，中国是目前研究影响最大的国家。中国目前是该领域发表论文最多的国家，但研究影响力不足。目前高被引文献的研究主要集中在对元宇宙的技术和历史回顾，以及元宇宙在教育领域的发展。人工智能和 utaut2 是该研究领域被引文献的基本集群。已经形成了虚拟现实、增强现实、混合现实、数字孪生和人工智能等几个研究热点。结语目前各领域对元宇宙的研究基本处于起步阶段，但未来发展潜力巨大，将逐步向多个不同方向渗透，面临诸多挑战。

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来源期刊

Journal of Big Data Computer Science-Information Systems

CiteScore

17.80

自引率

3.70%

发文量

105

审稿时长

13 weeks

期刊介绍： The Journal of Big Data publishes high-quality, scholarly research papers, methodologies, and case studies covering a broad spectrum of topics, from big data analytics to data-intensive computing and all applications of big data research. It addresses challenges facing big data today and in the future, including data capture and storage, search, sharing, analytics, technologies, visualization, architectures, data mining, machine learning, cloud computing, distributed systems, and scalable storage. The journal serves as a seminal source of innovative material for academic researchers and practitioners alike.