Research on Educational Metaverse (Edu-Metaverse) has developed into an active research field. Based on 310 academic papers published from 2004 to 2022, this study identifies contributors, scientific cooperations, and research themes using bibliometrics, social network analysis, topic modeling, and keyword analysis. Results suggest that Edu-Metaverse has gained increasing attention in academia since 2019. Countries/affiliations located in the same regions are close partners in scientific cooperation. By jointly interpreting topic modeling and keyword analysis results, this study reveals eight main themes in the field of Edu-Metaverse: 1) metaverse-based physical education, 2) metaverses-supported simulations for collaborative problem-based learning (PBL) in health/medical education, 3) three-dimensional virtual learning environment-supported art appreciation and creation in art education, 4) metaverse-enabled laboratories for STEM education, 5) language and 21st-century skill development through metaverse-supported immersive language learning, 6) metaverse for developing autism children' social communication abilities, 7) virtual world metaverse-supported gameful experience-based education, and 8) quantitative research on Edu-Metaverse focusing on learners' experience. We also identified challenges and directions needing further attention: 1) data security and privacy protection, 2) balance between the real world and virtual world identities, 3) preparing instructors for Edu-Metaverse, and 4) assessment of higher-order thinking competencies in Edu-Metaverse-based PBL. This work helps facilitate researchers' and practitioners' understanding of Edu-Metaverse research and raises their awareness of research frontiers and future directions.

Natural language processing (NLP) has become an increasingly significant role in advancing medicine. Rich research achievements of NLP methods and applications for medical information processing are available. It is of great significance to conduct a deep analysis to understand the recent development of NLP-empowered medical research field. However, limited study examining the research status of this field could be found. Therefore, this study aims to quantitatively assess the academic output of NLP in medical research field. We conducted a bibliometric analysis on NLP-empowered medical research publications retrieved from PubMed in the period 2007–2016. The analysis focused on three aspects. Firstly, the literature distribution characteristics were obtained with a statistics analysis method. Secondly, a network analysis method was used to reveal scientific collaboration relations. Finally, thematic discovery and evolution was reflected using an affinity propagation clustering method. There were 1405 NLP-empowered medical research publications published during the 10 years with an average annual growth rate of 18.39%. 10 most productive publication sources together contributed more than 50% of the total publications. The USA had the highest number of publications. A moderately significant correlation between country’s publications and GDP per capita was revealed. Denny, Joshua C was the most productive author. Mayo Clinic was the most productive affiliation. The annual co-affiliation and co-country rates reached 64.04% and 15.79% in 2016, respectively. 10 main great thematic areas were identified including Computational biology, Terminology mining, Information extraction, Text classification, Social medium as data source, Information retrieval, etc. A bibliometric analysis of NLP-empowered medical research publications for uncovering the recent research status is presented. The results can assist relevant researchers, especially newcomers in understanding the research development systematically, seeking scientific cooperation partners, optimizing research topic choices and monitoring new scientific or technological activities.

Social media plays a more and more important role in the research of health and healthcare due to the fast development of internet communication and information exchange. This paper conducts a bibliometric analysis to discover the thematic change and evolution of utilizing social media for healthcare research field. With the basis of 4361 publications from both Web of Science and PubMed during the year 2008–2017, the analysis utilizes methods including topic modelling and science mapping analysis. Utilizing social media for healthcare research has attracted increasing attention from scientific communities. Journal of Medical Internet Research is the most prolific journal with the USA dominating in the research. Overly, major research themes such as YouTube analysis and Sex event are revealed. Themes in each time period and how they evolve across time span are also detected. This systematic mapping of the research themes and research areas helps identify research interests and how they evolve across time, as well as providing insight into future research direction.