The Development of Ontology in Hadith Studies: A Bibliometric Analysis

Variation in Results of Three Biology‐Focused Search Engines: A Case Study Using North American Tree Species

Hadith studies in Indonesia have lagged despite hadith being the second source of Islam. The question is how Muslim scholars and Islamic social organizations have contributed to developing hadith studies in Indonesia. To answer this, library research with an analytical approach was conducted to discover a description of their contributions. Data was gathered through a literature study, analyzing references written by Muslim scholars in Indonesia using inductive and content analysis. The result shows that the lag in hadith studies is due to the lack of attention from Muslim scholars and the limited resources of hadith. However, Hadith studies began to be experienced in the second half of the 19th Century, growing to the early 20th Century. This was, among others, driven by the purification of Islamic teachings and the critique of Orientalists who undermined hadith. In this context, Muslim scholars and Islamic social organizations in Indonesia have significantly contributed to the development of hadith studies, mainly through providing literature on hadith and its sciences. However, their approaches differ. Muslim scholars interpret hadith textually and contextually, while Islamic social organizations, except NU, primarily use a textual approach. NU, in contrast, applies both approaches in its deliberations.

Background:Fungal metabolites known as aflatoxin M1 (AFM1) are linked to contaminated milk and milk products. Consuming food contaminated with AFM1 poses major health risks and may even be fatal.Methods:The retrieved publications were categorized in this bibliometric study using the Web of Science (WoS) database Jan 1, 1970 to Nov 30, 2022 based on a variety of factors, including the time of publication of articles, citation totals, languages, research areas, countries, affiliations, funding agencies, journals, and keywords analysis to identify any hot and developing subjects. Additionally, VOSviewer software version 1.6.18 provided the bibliometric analysis of the global collaboration network and hot research themes.Results:Overall, 679 published documents were detected. Food Control was the top-line journal in publications on AFM1 research with 540 published articles, while the USA was the best productive country in AFM1 publications as well as the major country with the maximum co-authorship collaboration. This study ensures quantitative and qualitative analyses of the top 25 journals, most cited published articles, most relevant authors and title word occurrences in published documents on AFM1 publications. Over the past two decades, there has been an enormous rise for research conducted on global AFM1.Conclusion:The assessment of the historical state and development trend in AFM1 scientific research can serve as a roadmap for future research and eventually, serve as a foundation for bettering management practices for territorial decisions, healthcare, and dairy industries.

Purpose: This study aims to contribute to the body of knowledge in business and management by investigating bibliometric research included in the Web of Science (WoS) database. It evaluates bibliometric studies using both evaluative and relational approaches, focusing on key trends and methodologies in the fields of business and management. Methodology: The study utilized the WoS database to source 2,422 studies related to business and management, including categories such as Business, Management, Finance, and Operations Management Research. Both evaluative and relational approaches were employed: Evaluative Approaches: Analyzed citation patterns and research outputs. Relational Approaches: Included co-word, co-author, co-citation analysis, and bibliographic coupling, though used less frequently. The analysis was comprehensive, unrestricted by year, country, or region, and involved a review of abstracts and study content. Findings: Management and business are the most researched areas in bibliometric studies. Evaluative methods were more commonly applied than relational approaches. Relational methods highlighted frequent co-usage of terms such as "bibliometric analysis" and "management." The United States and England emerged as the most active countries in terms of collaborative authorship. Originality: This study provides a detailed overview of bibliometric research trends in business and management. By employing comprehensive, unrestricted analysis, it offers valuable insights into methodologies and collaboration patterns, serving as a useful resource for novice researchers. The findings enrich the literature by identifying key areas of focus and methodological preferences in bibliometric studies.

This bibliometric study on data mining in education synonymous with big educational data utilizes VOSviewer and Harzing’s Publish and Perish to analyze the metadata of 1,439 journal articles found in Scopus from 2010 to 2022. As bibliometric analyses in this field are lacking, this study aims to provide a comprehensive outlook on the current developments and impact of research in this field. This study employs descriptive and trends analysis, co-authorship analysis, co-citation analysis, co-occurrences of keywords, terms map analysis, and analysis of the impact and performance of publications. It also partially replicates a similar study conducted by Wang et al. (2022), who used the Web of Science (WoS) database. The study is reported in an article entitled ‘Big data and data mining in education: A bibliometrics study from 2010 to 2022’. Results show that data mining in education is a growing research field. There is also a significant difference between the publications in Scopus and WoS. The study found several research areas and topics, such as student academic performance prediction, e-learning, machine learning, and innovative data mining techniques, to be the core basis for collaborating and continuing current research in this field. These results highlight the importance of continuing research on data mining in education, guiding future research in tackling educational challenges.

Machine learning (ML) and artificial intelligence (AI) techniques are gaining popularity as effective tools for coronavirus disease of 2019 (COVID-19) research. These strategies can be used in diagnosis, prognosis, therapy, and public health management. Bibliometric analysis quantifies the quality and impact of scholarly publications. ML in COVID-19 research is the focus of this bibliometric analysis. A comprehensive literature study found ML-based COVID-19 research. Web of Science (WoS) was used for the study. The searches included "machine learning," "artificial intelligence," and COVID-19. To find all relevant studies, 2 reviewers searched independently. The network visualization was analyzed using VOSviewer 1.6.19. In the WoS Core, the average citation count was 13.6 ± 41.3. The main research areas were computer science, engineering, and science and technology. According to document count, Tao Huang wrote 14 studies, Fadi Al-Turjman wrote 11, and Imran Ashraf wrote 11. The US, China, and India produced the most studies and citations. The most prolific research institutions were Harvard Medical School, Huazhong University of Science and Technology, and King Abdulaziz University. In contrast, Nankai University, Oxford, and Imperial College London were the most mentioned organizations, reflecting their significant research contributions. First, "Covid-19" appeared 1983 times, followed by "machine learning" and "deep learning." The US Department of Health and Human Services funded this topic most heavily. Huang Tao, Feng Kaiyan, and Ashraf Imran pioneered bibliographic coupling. This study provides useful insights for academics and clinicians studying COVID-19 using ML. Through bibliometric data analysis, scholars can learn about highly recognized and productive authors and countries, as well as the publications with the most citations and keywords. New data and methodologies from the pandemic are expected to advance ML and AI modeling. It is crucial to recognize that these studies will pioneer this subject.

Mobile health (m-Health) is widely acknowledged as a pivotal domain for improving global healthcare and driving its digital health transformation. Despite the vast amount of literature published in recent years, bibliometric studies on m-Health remain limited in scope and coverage. This study presents a comprehensive review of m-Health literature extracted from Scopus and PubMed databases, spanning the period from 1997 to 2023, including publications during the coronavirus disease 2019 (COVID-19) pandemic. The combined Scopus and PubMed databases were used in this study. The search formula for the literature retrieval used the most appropriate and relevant keywords to m-Health. The bibliometric data importation, extraction and analysis of authors, titles, publication date, publication place, publisher, volume number, issue number, citation count, document type, author keywords, affiliation were all carried out using the 'Biblioshiny', 'EndNote X9®', 'Microsoft Excel®' and 'Microsoft Access®' software tools. Duplicate records were manually identified and removed. Visualization maps illustrating the recurrent keywords, collaboration patterns, and prolific publishing countries were generated using 'VOSviewer®'. A total of 37,470 (20,703 from Scopus and 16,767 from PubMed) publications were selected for the literature analysis. The results provided the definitive literature evidence on the origin of the concept of m-Health in 2003. Significant increase in the publications followed the global surge of smart phones usage in 2007, and the emergence of m-Health applications (Apps) and their global markets and ecosystems. The number of the publications peaked between 2013 and 2022 with most citations in 2022. There was noticeable spike in m-Health literature during the COVID-19 pandemic. The results also showed that most of the highly cited publications, leading institutions, and most prolific authors were predominantly from the developed countries. The USA has the highest number of publications followed by the UK, Australia, Germany, Canada and China, with most of the prolific authors originating from these countries. In conclusion, while there has been a remarkable increase in global m-Health publications since 2003, most of the impactful literature and publications in this area originated from selected countries in the developed world. The study indicates a significant disparity between the published literature from developed compared to the developing countries. Addressing this disparity, further bibliographical studies are required to address these and other literature gaps.

O presente estudo bibliométrico tem como objetivo analisar a produção científica sobre a temática Vínculos Organizacionais, nas bases de dados Web of Science e Scopus (CAPES, 2020). Como método de pesquisa utilizou-se a análise bibliométrica de abordagem quantitativa e caráter descritiva. Foi levantamento de publicações no período de 2008 a 2019, os dados foram coletados na Web of Science e Scopus, utilizando-se como palavra-chave “vínculos organizacionais”. A análise ponderou os seguintes elementos: evolução temporal, número total de publicações, área temática, tipo de documento, países, principais autores e relatório de citação. Como método para análise dos dados foi utilizado o sistema VOSviewer, para criação de mapas textuais, clusters de co-citação e palavras chaves. Os resultados da pesquisa evidenciam que o tema é relevante, singularmente no período de 2008-2019, na área de negócios, gestão e contabilidade. Além disso, o estudo bibliométrico oportuniza que pesquisadores sejam capazes de desenvolver e ampliar o conhecimento neste campo de estudo. Como limitação do estudo, destaca-se a realização em apenas uma bases de dados, sugere-se que estudos futuros, ampliem a amostra abrangendo, eventos acadêmicos nacionais e internacionais, periódicos acadêmicos, bem como outras bases de dados científicos. Em relação às implicações práticas, o uso da bibliometria, contribui para medir os índices de produção e disseminação do conhecimento científico e divulgar o conhecimento.

Bibliometric analysis is crucial in understanding the evolution of research trends and knowledge in various fields. This study applies bibliometric analysis to explore the growth of the research paradigm on agility in the FinTech literature, using co-citation analysis and bibliographic coupling of selected articles. Based on this bibliometric analysis, the evolution of research on agility in the FinTech domain has been prepared, focusing on the literature related to FinTech agility between 1984 and 2022. In this study, we also address the limitations of individual analyses from Scopus and Web of Science (WOS) and propose a comprehensive approach by merging the two research databases. The results reveal significant disparities between authors, publication influences, and keyword occurrences between the WOS and merged databases. Our research highlights the importance of combining a database approach in bibliometric studies, providing valuable insights for scholars, researchers, and stakeholders. Finally, the in-depth bibliometric analysis demonstrates the significance of “FinTech agility” in the rapidly evolving FinTech sector. Financial technology companies’ agility, or ability to adapt quickly, is the foundation of their success and innovation.

Despite an increase in global research on the subject of Pemphigus, which seriously affects patient health and quality of life, there is no bibliometric research on this subject in literature to date. The aim of this study was to conduct a holistic analysis of scientific articles published on Pemphigus, using bibliometric methods. Articles published on the subject of Pemphigus between 1980 and 2021 were downloaded from the web of science (WoS) database and analyzed using various statistical methods. To determine trend subjects, collaboration between countries, and the most effective studies with citation analyses, visual network maps were obtained with bibliometric analyses. A total of 3034 articles were analyzed. The 3 countries making the greatest contribution to literature were the USA (n:831, 27.3%), Japan (n:402, 13.2%), and Germany (n:221, 7.2%). The 3 most active institutions were Keio University (n:163, 5.3%), Kurume University (n:130, 4.2%) and Tel Aviv University (n:107, 3.5%). The 3 journals publishing the most articles were the British Journal of Dermatology (n: 88), Journal of the American Academy of Dermatology (n:171) and the Journal of Investigative Dermatology (n:143). The 3 leading journals according to the mean number of citations (NC) per article (citation count: CC) were the New England Journal of Medicine (CC:246), the Lancet (CC:143) and the Journal of Cell Biology (CC:133). The author with the most articles published was Hashimoto Takashi (n.168, 5.5%). As a result of cluster analysis, it was seen that 9 different main clusters had been studied on Pemphigus subjects to date (1: desmoglein, 2: paraneoplastic Pemphigus (PNP) - Pemphigus types-desmosome, 3: desmoglein 1 ve 3-autoimmunity, 4: treatment-rituximab, 5: acantholysis-apoptosis, 6: quality of life-remission-relapse, 7: autoantibodies, 8: epidemiology-mortality, 9: corticosteroids). The most commonly studied subjects were determined to be pemphigus vulgaris (PV), pemphigus foliaceus (PF), autoimmunity, rituximab, PNP, desmoglein (desmoglein3-desmoglein1), autoantibodies, acantholysis, autoantibody, treatment, autoimmune disease, desmosome, ELISA, and immunofluorescence. The primary trending topic was rituximab drug, which is used in the treatment of Pemphigus. The other most studied trend topics were azathioprine drug used in treatment, intravenous immunoglobulin treatment, quality of life, mortality rates, Pemphigus herpetiformis, and wound healing.

Atopic dermatitis (AD) and allergic rhinitis (AR) are common allergic diseases that frequently co-occur, sharing common underlying pathophysiological mechanisms. This study retrieved comorbidity-related publications on AD and AR from the Web of Science (WOS) database over the past decade. Bibliometric analysis was performed using software tools including Microsoft Excel, VOSviewer, CiteSpace, and Scimago Graphica to examine countries, research institutions, journals, authors, and keywords. The results indicate that a total of 1571 relevant publications were published in the past 10 years, showing a fluctuating upward trend. The United States contributed the most publications (244 articles), cluster analysis identified 3 major research hubs, represented by the United States, China, and Germany. In terms of research institutions, China Medical University was the most productive (42 publications). Cluster analysis revealed 4 primary institutional research centers, represented by the University of Zurich, China Medical University, Seoul National University, and the University of Colorado. Among journals, Allergy published the most articles (56), while the Journal of Allergy and Clinical Immunology demonstrated the strongest academic influence, with an average of 78.77 citations per article. Regarding authors, Akdis, Cezmi A., had the highest output (15 publications), while Irvine, Alan D., exhibited the strongest impact, with a total citation count of 2711. Keyword analysis identified 11 clusters, which were primarily associated with immune regulation. This protocol provides researchers with an effective strategy to identify potential research gaps and guide future studies in these interrelated allergic diseases.

Objective: Acute respiratory distress syndrome (ARDS) is regarded as a serious complication with high mortality rates and constitutes an important health problem during the COVID-19 pandemic. Therefore, a thorough bibliometric study on ARDS is needed. In this study, it was aimed to holistically summarize the articles published on ARDS between the years 1980 and 2020 using statistical methods and bibliometric analyses.Material and Methods: The literature was scanned using the Web of Science (WoS) database. Keywords used on WoS included “acute respiratory distress syndrome”, “adult respiratory distress syndrome” and “ARDS”. The search was carried out on the “titles” of the publications, and the articles obtained were bibliometrically analyzed. Linear and non-linear regression analysis was used in order to estimate the number of future studies.Results: A total of 11.934 publications were found. Of these publications, 5402 were articles (45.3%) on which the bibliometric analysis was performed. A high increase trend was observed in the number of publications during COVID-19. Most articles were published in the field of Critical Care Medicine (1965, 36.4%). The top four countries contributing to the literature were the USA (1967, 36.4%), Germany (534, 9.9%), France (534, 9.9%), and China (534, 9.9%). The most active 4 institutions were confirmed as theUniversity of Toronto (154), University of California San Francisco (153), University of Washington (153) and University of Harvard (151). The first 2 journals with the most publications were Critical Care Medicine (394) and Intensive Care Medicine (248).Conclusion: In this comprehensive bibliometric study on ARDS on which the number of research increases day by day with the effect of the COVID-19 pandemic, a summarized information of 5402 articles published between 1980 and 2020 was reported. This study will be a guide for scientists and clinicians regarding the global output of ARDS.

HRMARS - Purpose: Industry 4.0 technologies, originating in Germany in 2011, have expanded rapidly across global manufacturing. However, high investment costs, rapid technological evolution, and a shortage of skilled professionals have constrained their adoption in many traditional sectors. The garment manufacturing industry, dominated by small and medium-sized enterprises and characterized by low automation, outdated equipment, and manual operations (Huynh, 2024), faces particular challenges. This study examines the current research status of Industry 4.0 technologies adoption in the traditional garment manufacturing sector and identifies future development directions. Design/methodology/approach: A systematic literature review combined with bibliometric analysis was employed. Relevant studies were retrieved from the Web of Science (WOS) database using defined keywords, and visualization was performed with VOSviewer 1.6.19 to map research hotspots and trends. Findings: The study provides a comprehensive overview of Industry 4.0 technologies adoption in garment manufacturing, highlighting current research focuses and emerging directions for future exploration. Research limitations/implications: Only five core Industry 4.0 technologies?Internet of Things, Cloud Computing, Big Data Analytics, Artificial Intelligence, and Smart Manufacturing?were analyzed. Future research could broaden this scope to capture a more holistic technological landscape. Practical implications: Industry 4.0 technologies adoption can transform traditional garment production, enhance competitiveness, and support sustainable development. Originality/value: By integrating five foundational Industry 4.0 technologies into a unified analytical framework, this study establishes a theoretical foundation for future empirical research on digital transformation within traditional garment manufacturing.

The aim of the study is to review the topic of competences that will be present at smart factories. The study used bibliometric and topic analysis to achieve insight into new trends in Industry 4.0. Bibliometric analysis and topic mining was done on 43 peer-reviewed journal articles and conference papers, published before July 2018 in the Thomson Reuters’ Web of Science and Scopus databases, using the software tool Statistica Data Miner. Results are segmented into four sections: (1) personnel development in learning organizations, (2) training techniques for personnel, (3) future engineering profiles and engineering education, and (4) relational capabilities. Each section is thoroughly discussed in this paper. The study contributes to the pool of knowledge on Industry 4.0 phenomena by compiling competences needed at smart factories in the future.

Objective: This study aims to explore the application of neural stem cells (NSCs) in the treatment of spinal cord injury (SCI) through a bibliometric analysis, identifying global research trends and hotspots in this field to further promote research progress. Methods: The bibliometric analysis was conducted using data from the Web of Science (WOS) database, focusing on literature published between 2000 and 2024. A total of 7010 related documents were retrieved, with 4531 specifically addressing NSCs and SCI. The analysis utilized the VOSviewer data analysis platform and the bibliometric online analysis platform to visualize publication and citation trends, keyword frequencies, and the contributions of various countries, authors and journals to the field. Results: The analysis revealed that the United States leads in SCI research, producing the most related articles, followed by China. Key research themes identified include “central nervous system”, “transplantation”, and “differentiation”. The most prolific journals in this field are the Cell Transplantation and Experimental Neurology, with the highest average citation rates observed in Nature Medicine. Okano H and Univ Toronto are the most influential author and institution, respectively. Conclusion: The bibliometric analysis underscores the growing global attention to SCI research and the importance of NSCs as a promising treatment avenue. Despite the challenges in understanding the SCI microenvironment and achieving clinical translation, significant progress has been made in stem cell preparation, in vitro culture, and differentiation methods. The study suggests that ongoing research and the development of comprehensive treatment strategies will enhance the clinical application of NSCs, offering hope for improved outcomes in SCI patients.