Co-authorship Analysis Research Articles

The evolution of precision agriculture and food safety: a bibliometric study

IntroductionFood safety issues pose a significant threat to humanity. Precision agriculture leverages advanced technologies for real-time monitoring and management, improving agricultural productivity and sustainability while safeguarding food security. Nonetheless, acquiring a thorough comprehension of this continually shifting panorama remains of vital significance.MethodsThis study conducts a comprehensive bibliometric review of precision agriculture and food safety, utilizing quantitative methods to identify past, current, and future evolution. It includes citation, co-authorship, co-citation, and co-words analyses.ResultsPublications emerged in 1994 and began to rise significantly since 2019. Citation analysis verified influencing works and journals, whereas co-authorship analysis identified how authors, institutions, and countries collaborate in this field. Co-citation analysis then classified past and current hotspots into four clusters: remote vegetation monitoring techniques, technological innovations and agricultural decision-making, precision agriculture and sustainable development, and deep learning in agriculture. After that, the co-occurrence of keywords revealed emerging trends, such as precision cultivation and yield prediction, smart agricultural technology and food management, precision information for climate change adaptation, and precision agriculture and food security.DiscussionThe findings provide insights for scholars, policymakers, researchers, practitioners, and industry stakeholders. They guide future research directions and address pressing challenges in agriculture and food safety.

Technological Innovations and Renewable Integration in Smart Cities: Enhancing Sustainability, Governance, And Security

The research focuses on the multiple ways in which technological innovation in the management, governance, and security of renewable energies contributes to making smart cities capable of integrating renewable energy systems that lead to more sustainable, efficient governance, and security resilience for the cities. A literature review of Scopus has been done with the aim of asserting at the juncture of smart cities, technological innovation, and renewable energy integration. Co-occurring and co-authorship analyses have been performed by VOSviewer for mapping the key research themes, collaborative networks, and research gaps. Core research themes include smart cities, IoT, renewable sources of energy, urban planning, AI, big data - lots of them, actually. Key areas for concern comprise cybersecurity, social equity, human-centered design, and adaptation to climate change. International collaborations identified through co-authorship analysis mirrored strong contributions from Pandolfi Alessandra and Galiulo Valentina. There are major knowledge gaps with respect to addressing, for example, how combining the elements of energy efficiency and cybersecurity under one umbrella could be defined as a smart city. Contribute uniquely in this area, and analyze the effects that the aggregate technological innovations and integration of renewable energy have on enhancing urban sustainability, governance, and security. These advances indicate ways in which urban systems can be optimized in order to enhance quality of life and lend to more sustainable and resilient urban environments. This study synthesizes interdisciplinary research in a novel manner in pointing out new areas that smart city development has barely touched upon.

VISUALISING TRENDS AND PATTERNS OF THREE DECADES OF RESEARCH ON MILLET PRODUCTION IN INDIA: A SCIENTOMETRICS ANALYSIS

This study analyses three decades of Millet Production research in India (1989-2023) with a Scientometrics approach, visualizing trends and patterns in scholarly output. India is the worlds largest producer of millet, with significant regional variations in millet cultivation. Major contributing states include Rajasthan, Karnataka, Maharashtra, and Madhya Pradesh. Scientometrics analysis, carried out on the Web of Science database using VOSviewer software, produced 600 publications with 12,028 citations. Development of millet research was found to be consistent with specific growth beginning after 2012, peaking during the International Year of Millets, 2023. Visualization of collaborative networks indicated the core institutions to be ICRISAT and ICAR. Prominent authors including Kumar A and Kumar S, and journals such as the Indian Journal of Agricultural Sciences are also featured in the Table. Keyword analysis showed that the research focus was on pearl millet, which primarily connects to agricultureand nourishment. Co-authorship and co-citation analyses underscore a robust collaborative environment in terms of research spanning several disciplines, concerning agronomy, biotechnology, and sustainable agriculture. This research focuses on the millet production research arena concerning food security, sustainable agricultural practices, and environmental challenges.

Consumer-Focused Financial Innovation and Marketing Strategies: A Three Decades Multidimensional Study Using Systematic Literature Review (SLR) and Bibliometric Analysis

This study examines how financial innovation affects consumer attitudes toward the use of technology in financial products and services. This study uses a bibliometric technique to analyze 34 years of publications from 1989 to 2023 on marketing strategies and financial innovations. Data were extracted from the Scopus and Dimensions databases to perform coauthorship and co-occurrence analyses. The VOSviewer software package, version 1.6.16, was used to analyze the data and analyzed the publications by identifying the most prominent journals, authors, articles, countries, keywords, citations, subject areas, and content analysis. The results show that innovation is the most trending keyword, followed by sustainable development, in the past 34 years. Moreover, the United States is in the first position, with most publications related to the field of financial innovation and marketing strategies, and ‘Marketing Strategy’ is a trending research topic in this field. The findings of this study will help policymakers in industries and government agencies take up financial innovations in distinct untapped areas and develop marketing strategies for the full development of the economy.

A bibliometric review of research on English as a medium of instruction (EMI), 1974–2022

ABSTRACT This bibliometric review employs science mapping to trace the development of the EMI-related literature and obtained 1378 relevant Scopus-indexed documents published between 1974 and 2022. The study uses co-author analysis, coupling analysis and co-occurrence analysis to reveal the co-authorship network, the most prolific authors, and the most commonly researched EMI topics. The result reveals a rapidly growing publication trajectory since the 2000s when global internationalisation became prominent. However, the overall outgrowth reaches a modest comfort. While this literature is worldwide in scope, publications in four countries – the United Kingdom, Hong Kong, Spain, and the United States – provided the most significant publications. Authors with the most publications and citations also come from these countries.

A Review and Bibliometric Analysis of Unmanned Aerial System (UAS) Noise Studies Between 2015 and 2024

Unmanned aerial systems (UAS), commonly known as drones, have gained widespread use due to their affordability and versatility across various domains, including military, commercial, and recreational sectors. Applications such as remote sensing, aerial imaging, agriculture, firefighting, search and rescue, infrastructure inspection, and public safety have extensively adopted this technology. However, environmental impacts, particularly noise, have raised concerns among the public and local communities. Unlike traditional crewed aircraft, drones typically operate in low-altitude airspace (below 400 feet or 122 m), making their noise impact more significant when they are closer to houses, people, and livestock. Numerous studies have explored methods for monitoring, assessing, and predicting the noise footprint of drones. This study employs a bibliometric analysis of relevant scholarly works in the Web of Science Core Collection, published from 2015 to 2024, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) data collection and screening procedures. The International Journal of Environmental Research and Public Health, Aerospace Science and Technology, and the Journal of the Acoustical Society of America are the top three preferred outlets for publications in this area. This review unveils trends, topics, key authors and institutions, and national contributions in the field through co-authorship analysis, co-citation analysis, and other statistical methods. By addressing the identified challenges, leveraging emerging technologies, and fostering collaborations, the field can move towards more effective noise abatement strategies, ultimately contributing to the broader acceptance and sustainable integration of UASs into various aspects of society.

Two decades of cross-border mergers and acquisitions research: A bibliometric analysis

Purpose The purpose of this study is to present the overall trend and dynamics in global mergers and acquisitions activity while suggesting future research avenues in this domain. The analysis covers two aspects to examine the main contours of the domain, that is performance analysis followed by thematic cluster analysis. Design/methodology/approach Bibliometric analysis has been used for examining 1,433 publications extracted from the Scopus database to identify the research trend between 2000 and 2021. With the help of VosViewer (a bibliometric software), bibliographic coupling, citation, co-authorship, keyword and network analysis have been carried out. Findings The analysis reveals that most of the research on cross-border mergers and acquisitions (CBMA) is concentrated in the context of developed markets, USA and UK being the largest. Most of the research till date is confined to wealth effects, value creation, corporate governance, socio-cultural aspects and various determinants of CBMA, all from the standpoint of the acquirer. Practical implications The present study highlights numerous opportunities for future research based on empirical analysis. There exists a dearth of studies around CBMA in the context of emerging nations which provides a relatively unexplored field to carry out research work. Originality/value The study makes use of a comprehensive list of keywords to have an extensive analysis. This is a pioneering study that has used bibliographic coupling of documents for content analysis and to the best of authors’ knowledge, no previous works on cross-border acquisitions have performed bibliographic coupling for this.

Artificial Intelligence and Deep Learning in Stock Prediction: A Bibliometric Review

Artificial intelligence (AI) and deep learning (DL) are advancing in stock market prediction, attracting the attention of researchers in computer science and finance. This bibliometric review analyzes 525 articles published from 1991 to 2024 in Scopus-indexed journals, utilizing VOSviewer software to identify key research trends, influential contributors, and burgeoning themes. The bibliometric analysis encompasses a performance analysis of the most prominent scientific contributors and a network analysis of scientific mapping, which includes co-authorship, co-occurrence, citation, bibliographical coupling, and co-citation analyses enabled by the VOSviewer software. Among the 693 countries, significant hubs of knowledge production include China, the US, India, and the UK, highlighting the global relevance of the field. Various AI and DL technologies are increasingly employed in stock price predictions, with artificial neural networks (ANN) and other methods such as long short-term memory (LSTM), Random Forest, Sentiment Analysis, Support Vector Machine/Regression (SVM/SVR), among the 1399 keyword counts in publications. Influential studies such as LeBaron (1999) and Moghaddam (2016) have shaped foundational research in 8159 citations. This review offers original insights into the bibliometric landscape of AI and DL applications in finance by mapping global knowledge production and identifying critical AI methods advancing stock market prediction. It enables finance professionals to learn about technological developments and trends to enhance decision-making and gain market advantage.

Mapping the Landscape of Biomechanics Research in Stroke Neurorehabilitation: A Bibliometric Perspective

Background/Objectives: The incorporation of biomechanics into stroke neurorehabilitation may serve to strengthen the effectiveness of rehabilitation strategies by increasing our understanding of human movement and recovery processes. The present bibliometric analysis of biomechanics research in stroke neurorehabilitation is conducted with the objectives of identifying influential studies, key trends, and emerging research areas that would inform future research and clinical practice. Methods: A comprehensive bibliometric analysis was performed using documents retrieved from the Scopus database on 6 August 2024. The analysis included performance metrics such as publication counts and citation analysis, as well as science mapping techniques, including co-authorship, bibliographic coupling, co-citation, and keyword co-occurrence analyses. Data visualization tools such as VOSviewer and Power BI were utilized to map the bibliometric networks and trends. Results: An overabundance of recent work has yielded substantial advancements in the application of brain–computer interfaces to electroencephalography and functional neuroimaging during stroke neurorehabilitation., which translate neural activity into control signals for external devices and provide critical insights into the biomechanics of motor recovery by enabling precise tracking and feedback of movement during rehabilitation. A sampling of the most impactful contributors and influential publications identified two leading countries of contribution: the United States and China. Three prominent research topic clusters were also noted: biomechanical evaluation and movement analysis, neurorehabilitation and robotics, and motor recovery and functional rehabilitation. Conclusions: The findings underscore the growing integration of advanced technologies such as robotics, neuroimaging, and virtual reality into neurorehabilitation practices. These innovations are poised to enhance the precision and effectiveness of therapeutic interventions. Future research should focus on the long-term impacts of these technologies and the development of accessible, cost-effective tools for clinical use. The integration of multidisciplinary approaches will be crucial in optimizing patient outcomes and improving the quality of life for stroke survivors.

Big Data in Tourism: A Bibliometric Analysis (2014-2024)

The emergence of big data and its related technologies has brought about novel economic models, industry phenomena, and relational networks, instigating revolutionary changes with significant value for tourism sustainability. This study conducts a bibliometric analysis of 212 articles (2014-2024) on big data in tourism from the Web of Science (WoS) Core Collection database, aiming to create a knowledge map based on big data in tourism. This study utilizes VOSviewer software to carry out citation analysis, co-citation analysis, co-authorship analysis, and keyword co-occurrence analysis, revealing trends in publications, national contributions, influential journals and authors, author collaborations, as well as the conceptual structure and research trends in the field of big data in tourism. The findings indicate a concentration of research in seven areas: machine learning, social network analysis, sustainability, tourism demand forecasting, artificial intelligence, smart tourism, and text mining techniques. The research has focused on emerging hot topics since 2022, including destination image, COVID-19, topic modeling, and urban tourism. This study maps the knowledge of big data in tourism, elucidates the academic evolution in this field, and offers future research directions for scholars in the domain.

Unveiling Scholarly Insights: Quality Assurance in Open and Distance Education

Open and distance education (ODE) has continuously evolved, significantly influencing educational, daily, and professional spheres, thereby prompting interest in its sustainability and quality. This study explored global scientific perspectives on quality assurance in ODE using the science mapping method. Search terms centred on open education, distance education, and quality assurance; data was gathered from 4,224 scientific texts in the Web of Science Core Collection. Analyses were conducted using VOSviewer software. Co-authorship analyses explored scientific collaboration structures at the country level. Globally shared concepts of interest to the scientific community were addressed using co-occurrence analyses. A detailed examination of co-occurrence outputs led to classification related to general and emerging key concepts. Results depicted a widespread global interest in quality assurance in ODE, fostering connections based on new cultural similarities. The concept of quality assurance in ODE continues to be enriched and developed, gravitating towards focused learning and instruction, establishing strong ties with various components of regular education as well as human elements. However, the prevailing view of quality assurance has yet to encompass this diversity. Rather than consider the nature and current potential of ODE, it has maintained an externalized and technical perspective.

Worldwide research trends on bone metastases of lung cancer: a bibliometric analysis.

Lung cancer has the highest fatality rate among all malignancies worldwide. Within this disease, bone metastasis (BM) emerges as a particularly deleterious site of metastatic dissemination, marked by a dismal prognosis. The objective of this investigation is to shed light on the current international research efforts and the development trajectory on lung cancer BM through a bibliometric analysis (performance and visualization analysis). Data were obtained from the Web of Science Core Collection repository on lung cancer BM from 1 January 2012 to 1 January 2022. Subsequently, the collected data underwent scrutiny using the VOSviewer software to reveal patterns of co-authorship, co-citation, and keyword analysis, while the CiteSpace software facilitated the generation of keyword cluster maps and performed burst analyses. The study included 327 papers of 2,154 authors, 587 organizations, and 41 countries, and explored the cooperation between them and the relationships between citations. Over the past decade, published papers showed a steady growth trend. China had the highest production with 189 papers, and USA had the highest collaboration with other countries, with 43 total link strength. Lung Cancer exhibited the highest frequency of co-cited journals, with a co-citation time of 412 and an IF/JCR partition of 6.081/Q1 in 2021. The most frequently co-cited article, authored by Tsuya A and published in Lung Cancer in 2007, amassed 70 co-citations. High-frequency keywords were categorized into four clusters: pathogenesis, treatment and clinical manifestations, prognosis, and diagnosis. In recent years, there has been a significant increase in the strong citation burst strength of keywords such as "predictor," "skeletal-related events," "efficacy," "migration," "docetaxel," and "impact." Lung adenocarcinoma is the most common type of tumor. This bibliometric study provides a comprehensive analysis of lung cancer BM in the recent 10 years. The field of early diagnosis, pathogenesis, and new treatments is entering a phase of rapid development and remains valuable for future research.

A bibliometric analysis of bladder cancer and microRNA research: Trends and advances from 2008 to 2022.

Bladder cancer (BC) is a significant global health issue with high incidence and mortality rates. MicroRNAs (miRNAs) play a crucial role in regulating gene expression and have been found to be dysregulated in BC. Understanding the role of miRNAs in BC development could lead to targeted therapies and improved patient management. Our study presents a thorough examination of the correlation between BC and miRNA research from 2008 to 2022. With the help of 3 powerful methods, including VOSviewer, Biblioshiny, and CiteSpace software, we analyzed the retrieved documents from "Core Collection databases online" on the Web of Science. In total, 798 articles were extracted from the Web of Science, and the number of published papers showed an upward trend from 2008 to 2019. The total number of citations was 21,233, of which the highest paper was a review article written by Chan Jiajia et al in 2018 with 752 citations. Based on the result of the coauthor analysis, Seki Naohiko was the most productive writer and China had the highest volume of published articles. Co-citation analysis was used to reveal the knowledge structure of the research field. In addition to the keywords "Bladder cancer" and "miRNA," "Proliferation," "Biomarkers," and "Apoptosis" were the high-frequency used keywords. Recently, increasingly researchers have paid more attention to the field about BC and miRNA around the worldwide. Through in-depth communication and close collaboration, the veil of miRNA in BC has gradually been unveiled. Bibliometric analysis helps to identify hotspots in research and areas for future investigation.

Forecasting Construction Cost Indices: Methods, Trends, and Influential Factors

The Construction Cost Index (CCI) is an important tool that is widely used in construction cost management to monitor cost fluctuations over time. Numerous studies have been conducted on CCI development and forecasting models, including time series, artificial intelligence, machine learning, and hybrid models. Therefore, this study seeks to reveal the complexity of CCI forecasting and identify the leading indicators, trends, and techniques for CCI prediction. A bibliometric analysis was conducted to explore the landscape in the CCI literature, focusing on co-occurrence, co-authorship, and citation analysis. These analyses revealed the frequent keywords, the most cited authors and documents, and the most productive countries. The research topics and clusters in the CCI forecasting process were presented, and directions for future research were suggested to enhance the prediction models. A case study was conducted to demonstrate the practical application of a forecasting model to validate its prediction reliability. Furthermore, this study emphasizes the need to integrate advanced technologies and sustainable practices into future CCI forecasting models. The findings are useful in enhancing the knowledge of CCI prediction techniques and serve as a base for future research in construction cost estimation.

Aggression in psychiatry: a bibliometric analysis

BackgroundAggression is a common problem in psychiatric clinics, and many studies have been conducted on the issue over the years. This study bibliometrically examines the characteristics and trends of aggression studies in psychiatry, such as the branches, publication years, types, publishers, and impact factors, and compares the focus areas of psychiatry and psychiatric nursing on aggression, to guide future research and readers on this topic. Bibliometric analysis was performed with network metrics, citation analysis, co-authorship analysis, science mapping, and network visualization techniques using WoS analysis reports and the VOSviewer program with data obtained from the Web of Science database on January 11, 2024.ResultsMost studies on aggression in psychiatry were published in 2019 as English articles. Then, 3.37% of these studies are in psychiatric nursing, mainly from Australia. In contrast, most psychiatric studies are from the USA. Psychiatry studies focus on causes, types, and relationships with psychiatric disorders, while psychiatric nursing studies emphasize aggressive attitudes, risk assessment, and aggression management.ConclusionsIt appears that studies on aggression continue to remain current in the literature and will continue to do so, considering that aggression is an ongoing clinical problem worldwide. Despite this, studies on assessing and managing the risk of aggression are still lacking. Future studies should prioritize the management of aggression. While the study showed the presence of multidisciplinary and international collaborations, it is recommended that these collaborations be further expanded. Findings may inform researchers’ keyword and journal choices.

Trends of machine learning for dental caries research in Southeast Asia: insights from a bibliometric analysis.

Dental caries is a common chronic oral disease, posing a serious public health issue. By analyzing large datasets, machine learning shows potential in addressing this problem. This study employs bibliometric analysis to explore emerging topics, collaborations, key authors, and research trends in Southeast Asia related to the application of machine learning in dental caries management. A comprehensive selection using the Scopus database to obtain relevant research, covering publications from inception to July 2024 was done. We employed the Bibliometric approaches, including co-authorship networks, yearly publishing trends, institutional and national partnerships, keyword co-occurrence analysis, and citation analysis, for the collected data. To explore the visualization and network analysis, we employed the tools such as VOSviewer and Bibliometrix in R package. The final bibliometric analysis included 246 papers. We found that Malaysia became the top contributor with 59 publications, followed by Indonesia (37) and Thailand (29). Malaysia had the highest Multiple Country Publications (MCP) ratio at 0.407. Top institutions including the Universiti Sains Malaysia led with 39 articles, followed by Chiang Mai University (36) and the National University of Singapore (30) became the leader. Co-authorship analysis using VOSviewer revealed six distinct clusters. A total of 1220 scholars contributed to these publications. The top 10 keywords, including 'human' and 'dental caries,' indicated research hotspots. We found growing evidence of machine learning applications to address dental caries in Southeast Asia. The bibliometric analysis highlights key authors, collaborative networks, and emerging topics, revealing research trends since 2014. This study underscores the importance of bibliometric analysis in tackling this public health issue.

Insights and networks: methodological assessment and scientometric analysis of economic evaluations in dentistry

IntroductionAssessing the methodological quality of economic evaluations (EEs) is crucial for evidence-based decision-making. The study aimed to evaluate EEs in restorative dentistry and endodontics, while also analyzing the scientific landscape of researchers and publications through co-authorship and citation network analysis providing an insight into the distribution of scientific expertise.MethodologyA systematic search for relevant articles from 2012 to 2022 was conducted using PubMed, Scopus, and EBSCO. The ten-point Drummond checklist was used to appraise the methodological quality of included studies. Bibliometric data for network analysis were extracted from the Dimensions database and visualized using VOSviewer software.ResultsOf the 37 articles, 81.08% scored good, 16.21% average, and 2.7% poor on the methodological rating scale. Most of the included studies were in Q1 journals, with limited representation in Q2 and Q3 journals. Compliance was highest in Q2 journals (95%), followed by Q1 (88.36%), while it dropped to 40% for Q3 journals. Co-authorship analysis revealed a dense network of researchers, with Prof. Falk Schwendicke V. having a significant influence. Moreover, the Journal of Dentistry had the highest impact, followed by Journal of Endodontics and BMC Oral Health.ConclusionsDespite a diverse scientific landscape, participation from developing countries was limited emphasizing the need for inclusivity and diversity in the scientific network. While the quantity of good-quality studies was encouraging, the overall quality of evidence remains paramount for decision-making in healthcare policy and practice. Therefore, continuous efforts to improve methodological rigor and reporting practices are essential to contribute robust evidence.

Trends of machine learning for dental caries research in Southeast Asia: insights from a bibliometric analysis

Background Dental caries is a common chronic oral disease, posing a serious public health issue. By analyzing large datasets, machine learning shows potential in addressing this problem. This study employs bibliometric analysis to explore emerging topics, collaborations, key authors, and research trends in Southeast Asia related to the application of machine learning in dental caries management. Methods A comprehensive selection using the Scopus database to obtain relevant research, covering publications from inception to July 2024 was done. We employed the Bibliometric approaches, including co-authorship networks, yearly publishing trends, institutional and national partnerships, keyword co-occurrence analysis, and citation analysis, for the collected data. To explore the visualization and network analysis, we employed the tools such as VOSviewer and Bibliometrix in R package. Results The final bibliometric analysis included 246 papers. We found that Malaysia became the top contributor with 59 publications, followed by Indonesia (37) and Thailand (29). Malaysia had the highest Multiple Country Publications (MCP) ratio at 0.407. Top institutions including the Universiti Sains Malaysia led with 39 articles, followed by Chiang Mai University (36) and the National University of Singapore (30) became the leader. Co-authorship analysis using VOSviewer revealed six distinct clusters. A total of 1220 scholars contributed to these publications. The top 10 keywords, including ‘human’ and ‘dental caries,’ indicated research hotspots. Conclusion We found growing evidence of machine learning applications to address dental caries in Southeast Asia. The bibliometric analysis highlights key authors, collaborative networks, and emerging topics, revealing research trends since 2014. This study underscores the importance of bibliometric analysis in tackling this public health issue.

Analyzing hockey publications through scientometric and altmetric perspectives

Purpose This study aims to present scientometric mapping and altmetric analysis of publications related to “Hockey” in the past three decades. By using the advanced analytical techniques of mapping coupled with altmetric analysis, this paper aims to reveal the complex network of collaborations, the dispersion of expertise worldwide and prevailing thematic trends in the field of hockey. Design/methodology/approach The data was extracted from the Web of Science (WoS) database and Altmetric Explorer for articles related to hockey over the past three decades. VOSviewer was used to conduct network analysis whereas MS-Excel was used for altmetric data analysis. The study focused on the articles retrieved using the key term “Hockey” in English language publications. The altmetric attention scores (AAS) were used to measure the level of online attention on different platforms, complementing traditional bibliometric analysis. Findings The study reveals a notable increase in the productivity of hockey research over the past 30 years, with a specific focus on major surges in publication output and altmetric attention in recent times. Coauthorship and country-wise mapping analysis highlight global research collaboration trends, while keyword analysis underscores thematic concentrations. Key journals such as British Journal of Sports Medicine and American Journal of Sports Medicine emerge as crucial dissemination platforms. The importance of X posts (Formerly Twitter) and Mendeley in the diffusion of hockey literature is highlighted by altmetric research. Originality/value The study provides a concise overview of research conducted on the game of hockey. This research will be advantageous for researchers and individuals involved in the hockey community, as it offers bibliographic insights and aids in identifying suitable media for disseminating their findings.

Bibliometric Analysis of Virtual Reality in Science Education over the Three Decades (1993-2023)

This study aims to conduct a bibliometric analysis of the use of virtual reality in science education over three decades (1993–2023). The method involved data from Google Scholar-indexed publications using Publish or Perish with keywords related to “virtual reality” and “education” over the past 3 decades. Nine hundred and eighty-six publications were obtained with a total of 131,130 citations with an average of 133 citations/paper and 4371 citations/year. The collected data were then screened to ensure its quality. Next, VOSviewer software was conducted to perform co-authorship and co-occurrence analysis. The results of the co-authorship analysis showed that there were 164 authors eligible to be visualized and divided into 88 clusters, indicating a high level of collaboration among authors in this field. Co-occurrence analysis shows that “virtual reality” has an occurrence of 696 in cluster 5 and “science education” is only 16 in cluster 2 with word networks formed only on the words “virtual reality,” “education,” and “field.” This study emphasizes the need for better VR in science education and more research on its impact on students’ science literacy. It outlines VR usage trends in scienceeducation, informing future studies. The findings particularly highlight the importance of investigating VR’s effectiveness in formal educational settings.