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1

Kumar, Rahul. "Bibliometric Analysis: Comprehensive Insights into Tools, Techniques, Applications, and Solutions for Research Excellence." Spectrum of Engineering and Management Sciences 3, no. 1 (2025): 45–62. https://doi.org/10.31181/sems31202535k.

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Bibliometric analysis has emerged as a vital methodology in understanding research landscapes through the application of statistical and quantitative techniques to academic literature. This study examines the evolution, significance, and application of bibliometric methods, highlighting their role in identifying influential authors, mapping collaboration networks, and uncovering emerging research trends. The analysis underscores the development of bibliometric tools, such as VOSviewer, CiteSpace, and Bibliometrix, and their diverse capabilities in visualizing and analyzing large datasets. By comparing bibliometric analysis with traditional review methodologies like systematic literature reviews and meta-analyses, this work illustrates its efficiency in providing comprehensive insights into research domains while emphasizing its complementary role in a holistic research approach. Through the lens of key challenges and advancements in bibliometric tools and methodologies, this research highlights its indispensable role in shaping academic, policy, and institutional strategies in a data-driven era.
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Ekasara, Adam Raka, Nuha Amiratul Afifah, Riska Aprilia Triyadi, Thema Arrisaldi, Daniel Radityo, and Hasan Tri Atmojo. "Tinjauan Literatur Sistematis dan Analisis Bibliometrik Penelitian Kerentanan Airtanah di Indonesia (2013-2021)." Jurnal Ilmiah Geologi PANGEA 9, no. 1sp (2022): 8. http://dx.doi.org/10.31315/jigp.v9i1sp.9404.

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Abstrak - Kebutuhan masyarakat terkait dengan airtanah semakin meningkat. Penilaian kerentanan airtanah menjadi salah satu cara untuk melindungi sumber daya airtanah agar tidak tercemar. Penelitian ini bertujuan untuk melakukan tinjauan literatur sistematis dan analisis bibliometrik untuk penelitian kerentanan airtanah di Indonesia menggunakan basis data Scopus. Parameter yang dianalisis berupa jumlah terbitan, sumber jurnal/prosiding, kata kunci dan jumlah kutipan. Dari hasil pencarian didapatkan 26 artikel dari 74 penulis pada rentang 2013-2021. Kata kunci populer yang muncul pada penelitian diantaranya groundwater pollution, groundwater vulnerability, groundwater resources, aquifers, dan groundwater. Pengolahan data dan visualisasi menggunakan aplikasi Bibliometrix dan VOSviewer. Dari hasil analisis disusun peta tematik yang menggambarkan 4 kuadran berdasarkan tingkat kepadatan dan tingkat sentralitas. Peta tematik ini diharapkan bisa menjadi acuan untuk penelitian kerentanan airtanah di Indonesia. Kata kunci: airtanah, analisis bibliometrik, Bibliometrix VOSviewerAbstract - The needs of the community related to groundwater are increasing. Assessing groundwater vulnerability is one way to protect groundwater resources from being polluted. This study aims to review systematic literature and bibliometric analysis for groundwater vulnerability research in Indonesia using the Scopus database. The parameters were analyzed through several publications, journals/proceedings, keywords and total citations. The search results found 26 articles from 74 authors in the range 2013-2021. Popular keywords that emerged in research include groundwater pollution, groundwater vulnerability, groundwater resources, aquifers, and groundwater. Data processing and visualization using the bibliometric and VOSviewer applications. The results of the analysis compiled a thematic map that describes 4 quadrants based on density and centrality levels. This thematic map is expected to be a reference for groundwater vulnerability research in Indonesia.Keywords: groundwater, bibliometric analysis, Bibliometrix VOSviewer
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Stuart, David. "Open bibliometrics and undiscovered public knowledge." Online Information Review 42, no. 3 (2018): 412–18. http://dx.doi.org/10.1108/oir-07-2017-0209.

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Purpose The purpose of this paper is to raise awareness of the potential of open bibliometrics, especially for the discovery of previously undiscovered public knowledge. Design/methodology/approach The viewpoint considers the limitations of the most popular current bibliometric tools and the possibilities offered from more open tools. It is supported by analysis of the openness of keywords associated with bibliometric studies in 2016. Findings The paper finds that although tools are emerging that offer more open bibliometrics, bibliometric research nonetheless continues to make use of restricted services. Originality/value This viewpoint on the potential of open bibliometrics is supported by an analysis of the current openness of bibliometric keywords.
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Ullah, Rahmat, Ikram Asghar, and Mark G. Griffiths. "An Integrated Methodology for Bibliometric Analysis: A Case Study of Internet of Things in Healthcare Applications." Sensors 23, no. 1 (2022): 67. http://dx.doi.org/10.3390/s23010067.

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This paper presents an integrated and easy methodology for bibliometric analysis. The proposed methodology is evaluated on recent research activities to highlight the role of the Internet of Things in healthcare applications. Different tools are used for bibliometric studies to explore the breadth and depth of different research areas. However, these Methods consider only the Web of Science or Scopus data for bibliometric analysis. Furthermore, bibliometric analysis has not been fully utilised to examine the capabilities of the Internet of Things for medical devices and their applications. There is a need for an easy methodology to use for a single integrated analysis of data from many sources rather than just the Web of Science or Scopus. A few bibliometric studies merge the Web of Science and Scopus to conduct a single integrated piece of research. This paper presents a methodology that could be used for a single bibliometric analysis across multiple databases. Three freely available tools, Excel, Perish or Publish and the R package Bibliometrix, are used for the purpose. The proposed bibliometric methodology is evaluated for studies related to the Internet of Medical Things (IoMT) and its applications in healthcare settings. An inclusion/exclusion criterion is developed to explore relevant studies from the seven largest databases, including Scopus, Web of Science, IEEE, ACM digital library, PubMed, Science Direct and Google Scholar. The study focuses on factors such as the number of publications, citations per paper, collaborative research output, h-Index, primary research and healthcare application areas. Data for this study are collected from the seven largest academic databases for 2012 to 2022 related to IoMT and their applications in healthcare. The bibliometric data analysis generated different research themes within IoMT technologies and their applications in healthcare research. The study has also identified significant research areas in this field. The leading research countries and their contributions are another output from the data analysis. Finally, future research directions are proposed for researchers to explore this area in further detail.
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Torres-Salinas, Daniel, and Nicolás Robinson-García. "The time for bibliometric applications." Journal of the Association for Information Science and Technology 67, no. 4 (2016): 1014–15. http://dx.doi.org/10.1002/asi.23604.

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Zhang, Jingru, Wan Ahmad Jaafar Wan Yahaya, and Mageswaran Sanmugam. "The Impact of Immersive Technologies on Cultural Heritage: A Bibliometric Study of VR, AR, and MR Applications." Sustainability 16, no. 15 (2024): 6446. http://dx.doi.org/10.3390/su16156446.

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This article aims to assist readers in understanding the current status of studies on the subject by providing a descriptive bibliometric analysis of publications on virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies in cultural heritage. A bibliometric analysis of 1214 publications in this discipline in the Scopus database between 2014 and the beginning of June 2024 was performed. We used VOSviewer and Bibliometrix as the analysis tools in this investigation. The outcome of this study provides a detailed overview of the descriptive bibliometric analysis based on seven categories, including the annual count of articles and citations, the most productive author, the primary affiliation, the publication source, and the subject areas. The contribution of this research lies in offering valuable insights for practitioners and researchers, helping them make informed decisions on the use of immersive technologies, for example, VR, AR, and MR, in the context of cultural heritage.
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Chio, Nayibe, and Eduardo Quiles-Cucarella. "A Bibliometric Review of Brain–Computer Interfaces in Motor Imagery and Steady-State Visually Evoked Potentials for Applications in Rehabilitation and Robotics." Sensors 25, no. 1 (2024): 154. https://doi.org/10.3390/s25010154.

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In this paper, a bibliometric review is conducted on brain–computer interfaces (BCI) in non-invasive paradigms like motor imagery (MI) and steady-state visually evoked potentials (SSVEP) for applications in rehabilitation and robotics. An exploratory and descriptive approach is used in the analysis. Computational tools such as the biblioshiny application for R-Bibliometrix and VOSViewer are employed to generate data on years, sources, authors, affiliation, country, documents, co-author, co-citation, and co-occurrence. This article allows for the identification of different bibliometric indicators such as the research process, evolution, visibility, volume, influence, impact, and production in the field of brain–computer interfaces for MI and SSVEP paradigms in rehabilitation and robotics applications from 2000 to August 2024.
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Panglipur, Indah Rahayu. "ANALISIS BIBLIOMETRIK: TREND PENELITIAN ETNOMATEMATIKA DI JEMBER PADA MATERI GEOMETRI." Prismatika: Jurnal Pendidikan dan Riset Matematika 7, no. 1 (2024): 29–37. https://doi.org/10.33503/prismatika.v7i1.171.

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This research aims at bibliometric analysis so that data can be obtained that can be used as a reference regarding the diversity of ethnomathematics in geometric concepts that have been explored through research to be developed in mathematics learning. The novelty obtained from this research is that it is able to provide an overview and reveal the trend position of ethnomathematics research on geometry material in Jember. The benefit obtained can be used as a reference for learning process activities carried out at school. This research uses bibliometric visualization and bibliometric analysis to provide a structural overview of the field of qualitative research. Bibliometrics uses the Publish or Perish (PoP) and VOSviewer applications to obtain a research trend database. The research results show that the concept of geometry is found in several publications related to ethnomathematics in Jember. Applications of concepts related to this research are triangles, symmetry, parallel lines, straight lines, curved lines, and applied to batik motifs.
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Rabbaje, Fatiha, Abdelmajid Ait Taleb, and Larbi Lasri. "Emerging Trends and Future Directions in Fused Deposition Modeling: A Bibliometric Analysis (2013-2023)." E3S Web of Conferences 601 (2025): 00030. https://doi.org/10.1051/e3sconf/202560100030.

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This bibliometric overview provides a detailed and comprehensive analysis of the research conducted on Fused Deposition Modeling (FDM) technology from 2013 to 2023. The analysis includes a thorough examination of publications, conference papers, and patents related to FDM technology. The overview offers valuable insights into the evolution, current state, and prospective trajectories of FDM technology. The analysis covers a wide range of topics related to FDM technology, including its applications, advancements, limitations, and prospects. This bibliometric overview aims to help researchers gain a deeper understanding of the FDM technology and its potential applications. It offers a comprehensive overview of the current state of research in the field and identifies new areas of research that could lead to significant advancements in FDM technology. The study utilized bibliometric indicators and network analysis methodologies, encompassing keyword analysis, citation metrics, journal productivity, associated publications, and author-related metrics. To conduct this analysis, two freely available software tools, VOSviewer and Bibliometrix [1], were employed.
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Du, Kai, Ao Li, Chen-Yu Zhang, Ren Guo, and Shu-Ming Li. "Platelet-rich plasma: A bibliometric and visual analysis from 2000 to 2022." Medicine 103, no. 46 (2024): e40530. http://dx.doi.org/10.1097/md.0000000000040530.

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Background: Platelet-rich plasma (PRP) is an integral biotherapeutic modality with evolving significance in the medical domain. Despite its expanding applications, a comprehensive bibliometric evaluation is essential to understand its development and impact. Methods: The Web of Science core collection subject search identified articles pertinent to PRP applications. Analytical tools, including CiteSpace, VOSviewer, Bibliometrix (R-Tool for R-Studio), TBtools, SCImago Graphica, Origin, and Excel, facilitated the bibliometric scrutiny. This examination spanned dimensions ranging from geographical and institutional contributions to thematic shifts and keyword prevalence. Results: A corpus of 5167 publications was analyzed, with the United States, particularly the Hospital for Special Surgery, emerging as major contributors. The American Journal of Sports Medicine was identified as the primary journal, and Anitua Eduardo as the leading author in the domain. Keyword analysis highlighted evolving research themes, with a shift from traditional applications in orthopedics and dentistry to emerging areas such as dermatology, aesthetics, and chronic pain management. Conclusion: The bibliometric analysis of PRP research reveals a multifaceted array of applications across various medical disciplines and highlights areas requiring further exploration, particularly in standardization, personalization, and safety. Future advancements in PRP research will necessitate innovative exploration, ethical considerations, and rigorous scientific validation to fully harness the therapeutic potential of PRP and related therapies.
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Tanted, Dr Nitin, Dr SumitZokarkar, Dr Deepesh Mahajan, and Dr GaganBhati. "A Bibliometric Review On Block Chain Technology Applications In Financial Services." International Journal of Environmental Sciences 11, no. 10s (2025): 766–80. https://doi.org/10.64252/7twbyz18.

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Blockchain technology has emerged as a disruptive innovation with significant implications for the financial services industry. This bibliometric review aims to analyze the academic literature on blockchain applications in financial services, identifying key trends, influential authors, and emerging research areas.This research contributes by offering a comprehensive overview of the blockchain's journey in financial services. Following the PRISMA approach, the authors meticulously curated relevant articles from the Dimension database. Bibliographic data were then meticulously assembled and analyzed using VOSviewer 1.6.20 and Bibliometrix version 4.3.0 employed to construct various network visualization maps, including co-authorship, citation, co-citation, bibliographic coupling, and term co-occurrence. The resulting network maps provided a comprehensive overview of the scholarly landscape, highlighting influential works, collaborative networks, and thematic clusters. By conducting a systematic review and bibliometric analysis, we aim to identify research gaps, influential authors, key themes and trends, thus providing a holistic understanding of blockchain's role in the financial sector. Paper also discusses the future scope in blockchain applications in fintech applications.
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Arash Salehpour. "Bibliometric Analysis of Deep Learning Applications in Diabetes." December 2022 4, no. 4 (2023): 291–306. http://dx.doi.org/10.36548/jtcsst.2022.4.006.

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This study provides a bibliometric review of deep learning applications in diabetes between 2018 and 2022, with an analysis of the 2201 publications. This review highlights the influential aspects of deep learning in diabetes research from a bibliometric perspective. Deep learning has drawn significant interest from researchers, particularly those working in diabetes. Two well-known databases: Web of Science and Scopus, each of which having its own data format, are combined into a single format using the R programming language in R Studio, and the duplicates are removed. The Bibliometrix package is used to conduct quantitative analysis, which includes highlighting the primary journals, the works that have been referenced the most, the authors, nations, and institutions that have produced the most, as well as keyword clustering, paper split into sub-periods to track theme progression, and top trend analysis. The findings demonstrate a notable increase in publications since 2018. A plethora of studies are conducted on the practical applications of deep learning to treat diabetes, which is dramatically rising. IEEE Access, Scientific Reports, and Computers in Biology and Medicine are the top three most relevant journals. China is most productive and its publications are highly cited, while the USA comes second. Accuracy, atrial fibrillation, and heart infarction have recently been the hot topics. The most frequently used words are human, article, and diabetes mellitus. The findings help academics better understand the study area in this related field, which is one of the hottest research fields in Artificial Intelligence.
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Munusamy, Lithish Raj Gopinath, Deepak Chandrasekar, Akshay Tandon, et al. "Bibliometric analysis of peer-reviewed literature on friction in orthodontics." SRM Journal of Research in Dental Sciences 15, no. 1 (2024): 32–38. http://dx.doi.org/10.4103/srmjrds.srmjrds_202_23.

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ABSTRACT Background: Orthodontics is a specialized field of dentistry that focuses on correcting maligned teeth and jaws. Friction in orthodontics occurs at multiple contact points along the archwire. We discuss the factors that affect friction in fixed appliances, including biological considerations, the ligation mechanism, the bracket, and the archwire. This bibliometric study’s objective is to review the literature on the subject of friction in orthodontics. This abstract provides an overview of the key concepts, methods, and applications of friction in orthodontics using bibliometric analysis. Methods: Bibliometrics can reveal significant shifts in research and publication trends. The Bibliometrix package with the VOS viewer program (Centre for Science and Technology Studies, Leiden University, The Netherlands), and RStudio 2021.09.0 + 351 for Windows (RStudio, Boston, Massachusetts) was used in the bibliometric research. The literary data for this study came from Elsevier’s Scopus database (www.scopus.com), and they were exported in BibTex format. The following criteria were used to independently classify the articles: (a) annual scholarly output; (b) top nations or regions; (c) top journals; (d) productive authors; (e) citations; (f) study design; (g) topic distribution; (h) keywords used; and (i) trending topics over time. Results: Brazil and Germany have the most single-country publications, according to a statistical analysis. Conclusions: The research done on the aspect of finding the role of friction in orthodontics provided data and knowledge about using friction as a tool to control tooth movement in fixed appliance therapy. Further studies are necessary to obtain more reliable results.
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Yeung, Andy Wai Kan, Anela Tosevska, Elisabeth Klager, et al. "Virtual and Augmented Reality Applications in Medicine: Analysis of the Scientific Literature." Journal of Medical Internet Research 23, no. 2 (2021): e25499. http://dx.doi.org/10.2196/25499.

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Background Virtual reality (VR) and augmented reality (AR) have recently become popular research themes. However, there are no published bibliometric reports that have analyzed the corresponding scientific literature in relation to the application of these technologies in medicine. Objective We used a bibliometric approach to identify and analyze the scientific literature on VR and AR research in medicine, revealing the popular research topics, key authors, scientific institutions, countries, and journals. We further aimed to capture and describe the themes and medical conditions most commonly investigated by VR and AR research. Methods The Web of Science electronic database was searched to identify relevant papers on VR research in medicine. Basic publication and citation data were acquired using the “Analyze” and “Create Citation Report” functions of the database. Complete bibliographic data were exported to VOSviewer and Bibliometrix, dedicated bibliometric software packages, for further analyses. Visualization maps were generated to illustrate the recurring keywords and words mentioned in the titles and abstracts. Results The analysis was based on data from 8399 papers. Major research themes were diagnostic and surgical procedures, as well as rehabilitation. Commonly studied medical conditions were pain, stroke, anxiety, depression, fear, cancer, and neurodegenerative disorders. Overall, contributions to the literature were globally distributed with heaviest contributions from the United States and United Kingdom. Studies from more clinically related research areas such as surgery, psychology, neurosciences, and rehabilitation had higher average numbers of citations than studies from computer sciences and engineering. Conclusions The conducted bibliometric analysis unequivocally reveals the versatile emerging applications of VR and AR in medicine. With the further maturation of the technology and improved accessibility in countries where VR and AR research is strong, we expect it to have a marked impact on clinical practice and in the life of patients.
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Romero Torres, Julian David. "Prolegomena for any Future Narrative Literaturemetrics." KOME 12, no. 2 (2024): 3–27. http://dx.doi.org/10.17646/kome.of.19.

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This paper introduces the concept of narrative literaturemetrics, a novel mixedmethods approach that applies the quantitative metrics traditionally used in bibliometrics to the field of literature. Utilising an extended version of Bourdieu’s field theory, this study draws parallels between academia and literature, emphasising the applicability of concepts such as capital, field, and agents to literary analysis. Despite the evident similarities, there has been a surprising lack of field-theoretical studies employing bibliometric methodologies within literary studies. This paper addresses that gap by outlining the theoretical foundations and methodological considerations of narrative literaturemetrics. It discusses adapting bibliometric indicators to literary analysis and highlights the distinctions necessary to respect the unique norms governing literature and academia. Furthermore, the paper explores the emerging qualitative turn in bibliometrics, particularly the development of narrative bibliometrics, and its relevance to the proposed approach. By detailing the conceptual framework and potential applications of narrative literaturemetrics, this study aims to establish a comprehensive model for future empirical research in literary studies.
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Freitas, Nichollas Rodrigues Bezerra, William Neves da Silva, João Pedro Mota Santana, Paulo Herbert França Maia Júnior, Vanja Fontenele Nunes, and Francisco Nivaldo Aguiar Freire. "Bibliometric Analysis of Publications on the Synthesis of Graphene and Reduced Graphene Oxide in the Scopus Research Platform." Revista de Gestão Social e Ambiental 18, no. 11 (2024): e09201. http://dx.doi.org/10.24857/rgsa.v18n11-071.

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Objective: Conduct a bibliometric analysis of articles on the synthesis of graphene and graphene oxide, as well as their applications, from the documents in the last fourteen years. Method: The bibliometric analysis used data from the Scopus database to visualize the main keywords, countries, and journals, addressing the theme of graphene synthesis and its applications over the past 14 years, from 2010 to 2024. Results and Discussion: Using the Bibliometrix software combined with R programming, 1,485 documents published in English were analyzed, which includes articles in review and in their final version. The results demonstrated that despite being a widely explored theme in the scientific community, there is still a growing global relevance. Research Implications: The analysis provided significant data on the development and key trends in academic research. The study revealed a great interest in obtaining reduced graphene oxide and its application in solar cells, as well as the efficiency they produce. Originality/Value: The study aimed to contribute to academic research by demonstrating and analyzing the main trends in graphene synthesis and its applications. Demonstrating its relevance in recent years and the growth in applications in photovoltaic systems.
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Farooq, Muhammad, Hikmat Ullah Khan, Tassawar Iqbal, and Saqib Iqbal. "An index-based ranking of conferences in a distinctive manner." Electronic Library 37, no. 1 (2019): 67–80. http://dx.doi.org/10.1108/el-03-2018-0064.

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Purpose Bibliometrics is one of the research fields in library and information science that deals with the analysis of academic entities. In this regard, to gauge the productivity and popularity of authors, publication counts and citation counts are common bibliometric measures. Similarly, the significance of a journal is measured using another bibliometric measure, impact factor. However, scarce attention has been paid to find the impact and productivity of conferences using these bibliometric measures. Moreover, the application of the existing techniques rarely finds the impact of conferences in a distinctive manner. The purpose of this paper is to propose and compare the DS-index with existing bibliometric indices, such as h-index, g-index and R-index, to study and rank conferences distinctively based on their significance. Design/methodology/approach The DS-index is applied to the self-developed large DBLP data set having publication data over 50 years covering more than 10,000 conferences. Findings The empirical results of the proposed index are compared with the existing indices using the standard performance evaluation measures. The results confirm that the DS-index performs better than other indices in ranking the conferences in a distinctive manner. Originality/value Scarce attention is paid to rank conferences in distinctive manner using bibliometric measures. In addition, exploiting the DS-index to assign unique ranks to the different conferences makes this research work novel.
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Alvarado-Silva, Carlos A. "The Virtual Teaching in Statistics Course in Higher Education: A Bibliometric Analysis and Systematic Literature Research." International Journal of Information and Education Technology 14, no. 2 (2024): 333–44. http://dx.doi.org/10.18178/ijiet.2024.14.2.2055.

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The research presents a bibliometric review aimed at understanding the most effective educational practices for teaching statistics in a virtual setting. It identifies the primary scopes, achievements, and challenges associated with this recent approach. To achieve this, the study explores articles published in journals indexed in databases like Scopus and Web of Science between 2017 and 2023. These articles offer recommendations based on evidence-backed pedagogical practices. Out of the scrutinized articles, 50 studies aligning with inclusion criteria were analyzed. These studies were subjected to a bibliometric approach and systematic literature research supported by the R bibliometrix software. This software was utilized to identify various research trends. Based on the study results, the analysis grouped teaching methods that exhibit greater efficacy in the virtual learning of the statistics.
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Camelia, Delcea. "Grey systems theory in economics – bibliometric analysis and applications’ overview." Grey Systems: Theory and Application 5, no. 2 (2015): 244–62. http://dx.doi.org/10.1108/gs-03-2015-0005.

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Purpose – The purpose of this paper is to synthesize the review of the existing literature attached to the grey economic system theory and applications and aims to offer a comprehensive picture of the contribution brought by the researchers to this particular field. Also, the paper underlines the main research areas within the grey economic theory and applications and serves as an informative summary kit for future research works and research directions. Design/methodology/approach – For appreciating the scientific progress made since the grey systems theory has been initiated to the present, with an accent on the literature dedicated to the economic field, a bibliometrics analysis has been conducted. The Perish or Publish software was used for extracting the needed data from Google Scholar for the entire period since the appearance of grey systems to now-a-days. In addition, an ISI Web of Science (WoS) search has been performed for extracting the grey economic papers. As the main focus is on the economic subject area of the grey systems, only the papers related to this field have been selected. Findings – The total number of grey economic paper from both Google Scholar and ISI WoS database, the number of authors, some citation metrics, H-index, authors’ provenience country, papers’ language, etc., have been presented and analysed. Also, a list with the most cited papers in the grey economic relational analysis, grey economic prediction models and grey economic incidence is putted forward. Practical implications – Through the bibliometric analysis on grey economic papers written over time, a qualitative analysis was performed on this field in order to underline the main research direction, to analyse what has been done in this field and to determine which can be the next research directions that can emerge from here. Originality/value – The paper succeeds in enlarging the view regarding the usage of grey systems theory in the economic field, offering a suitable analysis on the considered areas. Even though bibliometrics analysis have been conducted on the grey systems theory field, a grey economic bibliometric analysis has not been done yet, to the authors’ knowledge. Therefore, a synthesized of the existing literature attached to the grey economic system theory and applications is presented in order to offer a more comprehensive picture of the contribution brought by the researchers to this particular field.
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Cuciureanu, G., N. Turcan, Ir Cojocaru, and Ig Cojocaru. "Excellence or Misconduct: How the Visibility of Team Leaders Impacts the Research Project Competition in the Republic of Moldova?" Science and Innovation 19, no. 2 (2023): 3–16. http://dx.doi.org/10.15407/scine19.02.003.

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Introduction. Distributing public funds to the “best” researchers is a key element of the science policy. Evaluation is a fundamental activity for the allocation of competitive funding. The flaws of peer review have led to increased interest in the use of bibliometric indicators for the evaluation of the research project proposals.Problem Statement. The advantajes and advance of bibliometrc is stimulated interest toward the correlation of peer review and applicants’ bibliometric indicators. The results of such studies are different and heterogeneous. Such studies are insufficient in Eastern Europe.Purpose. To establish the correlation between peer review and bibliometric indicators of project team leaders within the call for research projects in Moldova, which are financed from public funds for 2020—2023.Material and Methods. Statistical correlation of the results of national competition of R&D proposals (evaluation and funding) and the bibliometrics indicators of project team leaders (publications ant patents); analytical analysis of the contextual factors influencing this correlation.Results. The results of the analysis have shown a positive, albeit weak correlation between the scores assigned by experts and the previous performances of leaders. The most significant relation is between the call results and the Hirsh index in Web of Science and Scopus databases. However, the projects proposed by the most cited researchers in WoS and Scopus or the founders of scientific schools did not receive funding.Conclusions. The analysis of the national R&D competition has proved that previous scientific performance of team leaders influenced the evaluation results and the funding of project proposals. However, these dependencies are not linear and seem to be affected by the conflicts of interest and “old boys” schemes. This fact calls for significant changes of the process: ensuring the transparency, the involvement of foreign experts and the use of bibliometric indicators in evaluation.
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Morriello, Rossana. "Peer review in research assessment and data analysis of Italian publications in SSD M-STO/08 (Archival science, bibliography, library science)." JLIS.it 14, no. 1 (2022): 99–120. http://dx.doi.org/10.36253/jlis.it-510.

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Since the introduction of research assessment systems at institutional level in the 1980s, the ongoing debate on the roles and functions of peer review and bibliometrics has been vivid and lively. In the first part of the article, the main lines over time of this debate are traced, and a reflection on the epistemic functions of peer review and citations is proposed. In Italy, the first research assessment exercise (VTR) was based on peer review only, while the following ones (VQR) were based on different methods for bibliometric disciplines and non-bibliometric disciplines, namely bibliometric indicators and peer review. Starting from a data analysis on Italian publications, and using as a sample data from M-STO/08 (Archival science, bibliography and library science) area, the essay shows some trends and changes in publication habits in HSS. Conclusions open a perspective on revitalization of peer review as a solid qualitative method for research assessment.
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Bravo Hidalgo, Debrayan, Reiner Jiménez Borges, and Yarelis Valdivia Nodal. "Applications of Solar Energy: History, Sociology and last Trends in Investigation." Producción + Limpia 13, no. 2 (2018): 21–28. http://dx.doi.org/10.22507/pml.v13n2a3.

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The increase in global energy demand, environmental problems and geopolitical tensions due to the control of finite conventional energy resources; these are reasons that have currently focused the attention of scientists on the applications of solar energy. The objective of this contribution is to reflect the trends in research regarding applications of solar energy. The materials and methods used in this investigation consisted of a search and bibliometric analysis carried out in the academic directory Scopus. A group of publications was detected under specific search criteria. The information detected was processed with text mining elements in the visualization software and bibliometric map exploration of VOSviewer science. The article dead sections, records of the first applications of solar energy, the social environment of solar energy applications, the first scientific meetings of global connotation in this subject, and bibliometrics of scientific activity focused on the applications of solar energy in the 21st century. As a result of the research, a sociological and anthropological vision of the man / energy interaction is exposed; This complements lines of research such as sustainable production and consumption, energy management and climate change. Conclusions: The trend in these investigations today, is to growth, and are focused on: heating and cooling of buildings, electric power generation, both in concentrated and distributed forms; and energy conversion for industrial processes.
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Hussin, M. S. F., M. I. Idris, H. Z. Abdullah, K. A. Azlan, and E. Mohamad. "Worldwide trends on hydroxyapatite from animal waste for biomedical applications – a bibliometric analysis (2012-2022)." IOP Conference Series: Earth and Environmental Science 1267, no. 1 (2023): 012001. http://dx.doi.org/10.1088/1755-1315/1267/1/012001.

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Abstract Hydroxyapatite plays a crucial role in the sustainable development of biomedical applications in recent years. Publication related to hydroxyapatite as filler for biopolymers has increasing trend with the expanding research output. Based on Scopus database, a bibliometric analysis was conducted to characterize the body of knowledge on hydroxyapatite for biomedical applications between 2012 and 2022. Bibliometric methods and knowledge visualization technologies were implemented to investigate the publication diversion. Analysis using bibliometric analysis found that 2,023 papers were determined with the keyword “hydroxyapatite” and “biomedical applications” between 2012 and 2022. The number of publications that relates to them has increased almost three-fold between 2012(99) to 2022(289). India, China, Malaysia, and the United States are the most productive countries, while Periyar University and University Politehnica of Bucharest are the most important institutions related to hydroxyapatite and biomedical applications. Ceramics International is the most productive journal followed by Materials Science & Engineering C. Bibliometric analysis would be a great assistant in giving scientific insight to support desired future research works, not only associated with biomedical applications.
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Velez Miñano, Leslie Yamilet, and Jennifer Camila Fernandez Baca. "Técnicas de extracción de colágeno: Aplicaciones y tendencias científicas." Manglar 21, no. 3 (2024): 391–99. http://dx.doi.org/10.57188/manglar.2024.043.

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The extraction of collagen from poultry by-products represents an innovative solution for waste management and the production of high added value bioproducts. This study reviews collagen extraction methods, with emphasis on hydrolysis, and their applications in the food, biomedical, and cosmetic industries. A bibliometric analysis was performed using the Scopus database and the VosViewer and Bibliometrix tools to identify research trends and international collaboration. The objective was to provide an overview of the current state of research on collagen extraction from animal tissues and its applications. The results show a growing global interest in this field, with China and Brazil leading in number of publications. An evolution is observed in extraction methods, from traditional approaches to more efficient and sustainable techniques. The conclusions highlight the potential of collagen extracted from by-products to promote sustainability and innovation in various industries, as well as the importance of international collaboration and interdisciplinary research to drive significant advances in this field
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Judijanto, Loso, and Restu Auliani. "Bibliometric Analysis of Biotechnology Development." West Science Nature and Technology 2, no. 02 (2024): 108–17. http://dx.doi.org/10.58812/wsnt.v2i02.992.

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This study utilizes bibliometric analysis to explore the landscape of biotechnology research from a comprehensive perspective, focusing on thematic clusters, research trends, research opportunities, and author collaboration networks. Through a series of visualizations created using VOSviewer, we identify four major thematic clusters: industrial applications, agricultural biotechnology, biotechnological processes, and commercial development. Our temporal analysis traces the progression from foundational research towards advanced applications and industry integration, occurring over the last two decades. The research opportunities identified include expanding studies in underrepresented areas like microalgae, biodiversity, and innovative biotechnological tools. Additionally, our analysis of author collaborations reveals diverse patterns, ranging from tight-knit groups to independent researchers, indicating varied collaborative dynamics. The findings provide a nuanced understanding of the evolution, current state, and emerging trends within biotechnology, offering valuable insights for future research directions and strategic industry applications.
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Kumar, Anil, Anupam Kumar, Mamta Sharma, Homraj Anand Rao Sahare, and Himanshu Jangid. "A Bibliometric Analysis of Bougainvillea Plant: Research Trends, Geographic Distribution and Future Direction." International Journal of Experimental Research and Review 42 (August 30, 2024): 18–32. http://dx.doi.org/10.52756/ijerr.2024.v42.002.

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The main aim of this paper is to conduct an exhaustive bibliometric analysis of Bougainvillea. A total of 624 publications on Bougainvillea were identified from Scopus data ranging from 1937 to 2024. The dataset downloaded from the Scopus database contains contributions from 2140 authors. Data visualization and analysis were carried out through different software: Microsoft Excel, Bibliometrics, BibExcel, VOSviewer, and Biblioshiny in R Studio. Analysis shows that the number of publications on Bougainvillea has increased tremendously in recent years, with 243 articles published between 2017 and 2024. India is the most significant contributor to Bougainvillea research. This bibliometric analysis helps a researcher gain direction into the key trends and areas of interest while exploring the medicinal attributes of the plant. Bougainvillea, a plant more commonly associated with its colourful blooms and ornamental use, has recently been gaining attention for its medicinal applications. The present review attempts to garner such existing knowledge regarding the medicinal attributes of Bougainvillea related to its phytochemical composition, traditional uses, pharmacological activities, and therapeutic applications.
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Basílio, Marcio Pereira, Valdecy Pereira, Helder Gomes Costa, Marcos Santos, and Amartya Ghosh. "A Systematic Review of the Applications of Multi-Criteria Decision Aid Methods (1977–2022)." Electronics 11, no. 11 (2022): 1720. http://dx.doi.org/10.3390/electronics11111720.

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Multicriteria methods have gained traction in academia and industry practices for effective decision-making. This systematic review investigates and presents an overview of multi-criteria approaches research conducted over forty-four years. The Web of Science (WoS) and Scopus databases were searched for papers on multi-criteria methods with titles, abstracts, keywords, and articles from January 1977 to 29 April 2022. Using the R Bibliometrix tool, the bibliographic data was evaluated. According to this bibliometric analysis, in 131 countries over the past forty-four years, 33,201 authors have written 23,494 documents on multi-criteria methods. This area’s scientific output increases by 14.18 percent every year. China has the highest percentage of publications at 18.50 percent, followed by India at 10.62 percent and Iran at 7.75 percent. Islamic Azad University has the most publications with 504, followed by Vilnius Gediminas Technical University with 456 and the National Institute of Technology with 336. Expert Systems With Applications, Sustainability, and the Journal of Cleaner Production are the top journals, accounting for over 4.67 percent of all indexed works. In addition, E. Zavadskas and J. Wang have the most papers in the multi-criteria approaches sector. AHP, followed by TOPSIS, VIKOR, PROMETHEE, and ANP, is the most popular multi-criteria decision-making method among the ten nations with the most publications in this field. The bibliometric literature review method enables researchers to investigate the multi-criteria research area in greater depth than the conventional literature review method. It allows a vast dataset of bibliographic records to be statistically and systematically evaluated, producing insightful insights. This bibliometric study is helpful because it provides an overview of the issue of multi-criteria techniques from the past forty-four years, allowing other academics to use this research as a starting point for their studies.
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Li, Zhiyi. "The Value of GeneXpert MTB/RIF for Detection in Tuberculosis: A Bibliometrics-Based Analysis and Review." Journal of Analytical Methods in Chemistry 2022 (October 15, 2022): 1–11. http://dx.doi.org/10.1155/2022/2915018.

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With the continuous development of medical science and technology, especially with the advent of the era of precision diagnosis and treatment, molecular biology detection technology is widely valued and applied as an aid to early diagnosis of tuberculosis. The GeneXpert Mycobacterium tuberculosis Branching (MTB) technology is a suite of semi-nested real-time fluorescent quantitative PCR in vitro diagnostic technologies developed by Cepheid Inc. It targets the rifampicin resistance gene, rpoB, and can detect both MTB and resistance to rifampicin within 2 h. This review analyzed the papers related to GeneXpert using bibliometric software CiteSpace and Bibliometrix. A total of 151 articles were analyzed, spanning from 2011 to 2021. This bibliometrics-based review summarizes the history of the development of GeneXpert in tuberculosis diagnosis and its current status. Contributions of different countries to the topic, journal analysis, key paper analysis, and clustering of keywords were used to analyze this topic.
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Williams, Jessica R., Dalia Lorenzo, John Salerno, Vivian M. Yeh, Victoria B. Mitrani, and Sunil Kripalani. "Current applications of precision medicine: a bibliometric analysis." Personalized Medicine 16, no. 4 (2019): 351–59. http://dx.doi.org/10.2217/pme-2018-0089.

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Galán, José Javier, Ramón Alberto Carrasco, and Antonio LaTorre. "Military Applications of Machine Learning: A Bibliometric Perspective." Mathematics 10, no. 9 (2022): 1397. http://dx.doi.org/10.3390/math10091397.

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The military environment generates a large amount of data of great importance, which makes necessary the use of machine learning for its processing. Its ability to learn and predict possible scenarios by analyzing the huge volume of information generated provides automatic learning and decision support. This paper aims to present a model of a machine learning architecture applied to a military organization, carried out and supported by a bibliometric study applied to an architecture model of a nonmilitary organization. For this purpose, a bibliometric analysis up to the year 2021 was carried out, making a strategic diagram and interpreting the results. The information used has been extracted from one of the main databases widely accepted by the scientific community, ISI WoS. No direct military sources were used. This work is divided into five parts: the study of previous research related to machine learning in the military world; the explanation of our research methodology using the SciMat, Excel and VosViewer tools; the use of this methodology based on data mining, preprocessing, cluster normalization, a strategic diagram and the analysis of its results to investigate machine learning in the military context; based on these results, a conceptual architecture of the practical use of ML in the military context is drawn up; and, finally, we present the conclusions, where we will see the most important areas and the latest advances in machine learning applied, in this case, to a military environment, to analyze a large set of data, providing utility, machine learning and decision support.
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Hincapie, Mauricio, Christian Diaz, Alejandro Valencia, Manuel Contero, and David Güemes-Castorena. "Educational applications of augmented reality: A bibliometric study." Computers & Electrical Engineering 93 (July 2021): 107289. http://dx.doi.org/10.1016/j.compeleceng.2021.107289.

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Yasin, Elham Tahsin, Mediha Erturk, Melek Tassoker Bulut, and Murat Koklu. "Bibliometric analysis of deep learning applications in dentistry." International Dental Journal 74 (October 2024): S216. http://dx.doi.org/10.1016/j.identj.2024.07.044.

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Allani, Hela, Ana Teresa Santos, and Honorato Ribeiro-Vidal. "Multidisciplinary Applications of AI in Dentistry: Bibliometric Review." Applied Sciences 14, no. 17 (2024): 7624. http://dx.doi.org/10.3390/app14177624.

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This review explores the impact of Artificial Intelligence (AI) in dentistry, reflecting on its potential to reshape traditional practices and meet the increasing demands for high-quality dental care. The aim of this research is to examine how AI has evolved in dentistry over the past two decades, driven by two pivotal questions: “What are the current emerging trends and developments in AI in dentistry?” and “What implications do these trends have for the future of AI in the dental field?”. Utilizing the Scopus database, a bibliometric analysis of the literature from 2000 to 2023 was conducted to address these inquiries. The findings reveal a significant increase in AI-related publications, especially between 2018 and 2023, underscoring a rapid expansion in AI applications that enhance diagnostic precision and treatment planning. Techniques such as Deep Learning (DL) and Neural Networks (NN) have transformed dental practices by enhancing diagnostic precision and reducing workload. AI technologies, particularly Convolutional Neural Networks (CNNs) and Artificial Neural Networks (ANNs), have improved the accuracy of radiographic analysis, from detecting dental pathologies to automating cephalometric evaluations, thereby optimizing treatment outcomes. This advocacy is underpinned by the need for AI applications in dentistry to be both efficacious and ethically sound, ensuring that they not only improve clinical outcomes but also adhere to the highest standards of patient care.
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Peng, Zhao, Run Zong Fu, Han Peng Chen, Kaede Takahashi, Yuki Tanioka, and Debopriyo Roy. "AI Applications in Emotion Recognition: A Bibliometric Analysis." SHS Web of Conferences 194 (2024): 03005. http://dx.doi.org/10.1051/shsconf/202419403005.

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This paper conducts a preliminary exploration of Artificial Intelligence (AI) for emotion recognition, particularly in its business applications. Employing adaptive technologies like machine learning algorithms and computer vision, AI systems analyze human emotions through facial expressions, speech patterns, and physiological signals. Ethical considerations and responsible deployment of these technologies are emphasized through an intense literature review. The study employs a comprehensive bibliometric analysis, utilizing tools such as VOSViewer, to trace the evolution of emotion-aware AI in business. Three key steps involve surveying the literature on emotion analysis, summarizing information on emotion in various contexts, and categorizing methods based on their areas of expertise. Comparative studies on emotion datasets reveal advancements in model fusion methods, exceeding human accuracy and enhancing applications in customer service and market research. The bibliometric analysis sheds light on a shift towards sophisticated, multimodal approaches in emotion recognition research, addressing challenges such as imbalanced datasets and interpretability issues. Visualizations depict keyword distributions in research papers, emphasizing the significance of “emotion recognition” and “deep learning.” The study concludes by offering insights gained from network visualization, showcasing core keywords and their density in research papers. Based on the literature, a SWOT analysis is also conducted to identify the strengths, weaknesses, opportunities, and threats associated with applying emotion recognition to business. Strengths include the technology’s high accuracy and real-time analysis capabilities, enabling diverse applications such as customer service and product quality improvement. However, weaknesses include data bias affecting the AI model’s quality and challenges in processing complex emotional expressions. Opportunities lie in the increasing number of studies, market size, and improving research outcomes, while threats include privacy concerns and growing competition.
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Cheng, Tiejun, Yongmei Pan, Ming Hao, Yanli Wang, and Stephen H. Bryant. "PubChem applications in drug discovery: a bibliometric analysis." Drug Discovery Today 19, no. 11 (2014): 1751–56. http://dx.doi.org/10.1016/j.drudis.2014.08.008.

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Arifin, Samsul. "A Bibliometric Study of 3D Printing's Educational Applications." JURNAL VOKASI TEKNOLOGI INDUSTRI (JVTI) 6, no. 1 (2024): 012–29. https://doi.org/10.36870/jvti.v6i1.361.

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Using 3D printing in education research will continue to grow over the next few years, according to experts. It may be seen in a broad variety of scientific fields as well. An examination of 1,384 3D printing research articles published in 793 scientific journals and authored by 5,438 authors was conducted in this study (103 single-authored documents and 5,335 multi-authored documents). The goal of this study is to identify the trending topic in 3D printing right now. R software's Bibliometrix tool was used to extract data from Scopus and run it via VOSviewer, which was then loaded into the database. We've chosen the world's most significant publications, journals, authors, nations, and affiliations based on citation analysis criteria. While keywords and phrases are likely to be the most important issues and conclusions of the research, it is probable that some major patterns and concerns contained in the complete text are not properly reflected in our study. The development of patterns in 3D Printing should be examined in future studies to give scientific knowledge, as well.
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Kalnina, Anete, Maksims Feofilovs, and Francesco Romagnoli. "Blockchain Technology Applications for Decarbonization: A Bibliometric Review." Environmental and Climate Technologies 29, no. 1 (2025): 137–55. https://doi.org/10.2478/rtuect-2025-0010.

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Abstract The integration of decentralized and digital technologies like blockchain in sectors that aim to fulfil certain decarbonization goals could be a promising solution to facilitate the transition to climate neutrality. With the aim to construct a comprehensive and systematic bibliometric analysis on the inclusion of blockchain technology in renewable energy, transport (electric vehicles) and agri-food industry, this paper provides an in-depth analysis of existing studies on these topics to identify future research opportunities. Using R-studio, Web of Science and Scopus data were analysed and visualized. The results of this study indicate growth of the publication count throughout the years. This research shows that the most productive countries are China and India, although the average citations per article is higher in United States of America and United Kingdom. Trend topics, thematic evaluation and co-occurrence network from this study suggest that the application of blockchain technology in analysed sectors should be combined with other digital solutions like Internet of Things and artificial intelligence to increase security, facilitate systems’ management and assist in policy planning. The identified research gaps are connected to blockchain technology and renewable energy storage systems (e.g., hydrogen), materials used in electric vehicles’ batteries and circularity (including life cycle and recycling) in the agri-food sector and other studied sectors.
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Khatoon, Rabeya, Jahanara Akter, Md Kamruzzaman, et al. "Advancing Healthcare: A Comprehensive Review and Future Outlook of IoT Innovations." Engineering, Technology & Applied Science Research 15, no. 1 (2025): 19700–19711. https://doi.org/10.48084/etasr.9156.

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Rapid innovation leading to better patient outcomes have been driven by recent breakthroughs in the Internet of Things (IoT), which have drastically changed the healthcare sector. In order to highlight the importance of IoT in healthcare applications, this article presents a user-friendly and integrated approach for bibliometric analysis. Traditional bibliometric methods often rely solely on Web of Science (WoS) or Scopus, limiting the scope of analysis. To address this issue, the proposed approach uses the R program Bibliometrix to combine data from seven databases, namely Scopus, WoS, IEEE, ACM Digital Library, PubMed, Science Direct, and Google Scholar (GS). After having developed an inclusion/exclusion criterion, 2,990 journal papers published between 2011 and 2022 were subjected to a thorough literature review and bibliometric analysis. This study demonstrates that the healthcare industry is highly interested in the IoT, as well as the rapid growth of research into IoT healthcare applications, blockchain, Artificial Intelligence (AI), 5G telecoms, and data analytics. Authentication methods, fog computing, cloud-IoT integration, cognitive smart healthcare, and other essential topics are further examined by employing co-citation network analysis. In addition to illuminating potential avenues for further investigation, these results provide academics with a comprehensive picture of where IoT research in healthcare is standing at the moment. The output of the conducted analysis shows that there has been a dramatic uptick in publishing since 2017, with most of the articles appearing in prestigious journals related to computer science. By integrating data from multiple databases, the proposed methodology represents a significant advancement in bibliometric analysis, enabling a more comprehensive exploration of IoT's impact on healthcare, and facilitating a deeper understanding of the emerging trends and critical themes in this rapidly evolving field.
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Hasan, Faizul, Hendrik Setia Budi, Lia Taurussia Yuliana, and Mokh Sujarwadi. "Trends of machine learning for dental caries research in Southeast Asia: insights from a bibliometric analysis." F1000Research 13 (October 3, 2024): 908. http://dx.doi.org/10.12688/f1000research.154704.2.

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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.
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Hasan, Faizul, Hendrik Setia Budi, Lia Taurussia Yuliana, and Mokh Sujarwadi. "Trends of machine learning for dental caries research in Southeast Asia: insights from a bibliometric analysis." F1000Research 13 (August 8, 2024): 908. http://dx.doi.org/10.12688/f1000research.154704.1.

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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.
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Hasan, Faizul, Hendrik Setia Budi, Lia Taurussia Yuliana, and Mokh Sujarwadi. "Trends of machine learning for dental caries research in Southeast Asia: insights from a bibliometric analysis." F1000Research 13 (October 11, 2024): 908. http://dx.doi.org/10.12688/f1000research.154704.3.

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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.
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Nofiyanti, Sri Handayani, Usman Ahmad, Yuvita Lira Vesti Arista, Michael Alexander Hutabarat, and Muhammad Rizqi. "Advancing Modified Atmosphere Packaging for Horticultural Products: A Systematic Review and Bibliometric Analysis." International Journal of Current Microbiology and Applied Sciences 14, no. 2 (2025): 1–16. https://doi.org/10.20546/ijcmas.2025.1402.001.

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The present study aimed to perform a bibliometric analysis regarding Modified Atmosphere Packaging (MAP) for horticultural products and its effectiveness in postharvest management. A literature search was conducted using the Scopus database with the keyword "Modified Atmosphere Packaging". The retrieved articles were imported into Mendeley software version 1.19.8 for attribute verification. A total of 117 articles met the inclusion criteria. The bibliometric database was analyzed using the Bibliometrix package on R version 4.2.2 and VOSviewer version 1.6.18. The analysis revealed that the most frequently occurring keywords included shelf life, food preservation, biodegradable packaging, gas composition, and smart monitoring systems. The most widely cited articles addressed gas composition optimization, postharvest quality maintenance, and sustainable packaging solutions. The USA, China, and India emerged as the leading contributors to MAP research. Despite its benefits, high costs, lack of standardization, and limited real-world applications pose challenges, particularly in regions with inadequate infrastructure. The study highlights emerging preservation techniques, such as high-pressure processing and ozone treatment, which enhance MAP’s effectiveness. Future research should focus on large-scale field trials, cost-effective innovations, and sustainability assessments to optimize MAP applications in postharvest management.
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Lv, Hai, Yangyang Liu, Huimin Yin, Jingzhi Xi, and Pingmin Wei. "Machine Learning Applications in Prediction Models for COVID-19: A Bibliometric Analysis." Information 15, no. 9 (2024): 575. http://dx.doi.org/10.3390/info15090575.

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The COVID-19 pandemic has had a profound impact on global health, inspiring the widespread use of machine learning in combating the disease, particularly in prediction models. This study aimed to assess academic publications utilizing machine learning prediction models to combat COVID-19. We analyzed 2422 original articles published between 2020 and 2023 with bibliometric tools such as Histcite Pro 2.1, Bibliometrix, CiteSpace, and VOSviewer. The United States, China, and India emerged as the most prolific countries, with Stanford University producing the most publications and Huazhong University of Science and Technology receiving the most citations. The National Natural Science Foundation of China and the National Institutes of Health have made significant contributions to this field. Scientific Reports is the most frequent journal for publishing these articles. Current research focuses on deep learning, federated learning, image classification, air pollution, mental health, sentiment analysis, and drug repurposing. In conclusion, this study provides detailed insights into the key authors, countries, institutions, funding agencies, and journals in the field, as well as the most frequently used keywords.
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Ab Rahim, Rosyawati, Taufik Ismail, Radhwa Abu Bakar, and Wan Azani Mustafa. "Arabic Vocabulary Applications Bibliometric Analysis from 1987 to 2024." Environment-Behaviour Proceedings Journal 10, SI24 (2025): 79–86. https://doi.org/10.21834/e-bpj.v10isi24.6367.

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This study analyzes the development and trends of Arabic vocabulary applications from 1987 to 2024 using bibliometric techniques.It examines 37 years of literature to address gaps in understanding their evolution and impact. Data were cited from databases such as SCOPUS as well as Web of Science, focusing on conference proceedings, articles, and reviews published within the defined timeframe. Various bibliometric indicators, VosViewer version 1.16.20 tools to analyze publication trends, citation counts, co-authorship networks, and thematic analysis were utilized to analyze the research landscape comprehensively. Findings highlight increasing publications, themes like gamification, and the shift to AI-powered tools, emphasizing future research directions.
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Delcea, Camelia, Adrian Domenteanu, Corina Ioanăș, Vanesa Mădălina Vargas, and Alexandra Nicoleta Ciucu-Durnoi. "Quantifying Neutrosophic Research: A Bibliometric Study." Axioms 12, no. 12 (2023): 1083. http://dx.doi.org/10.3390/axioms12121083.

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In recent years, neutrosophic theory has garnered increasing attention within scholarly circles due to its applicability in various domains. Within these domains, the field of decision-making has derived significant advantages from the progressions in neutrosophic theory. Notably, neutrosophic theory has made substantial contributions by advancing and offering a range of aggregation operators and information measures specifically designed for enhancing decision-making processes. In this context, this study aims to conduct a comprehensive bibliometric analysis of the current research landscape in the field of neutrosophic theory, with a specific focus on understanding its applications and development trends. Our analysis reveals that the scientific literature addresses neutrosophic theory in a diverse range of applications. This examination encompasses a scrutiny of key contributors, affiliated academic institutions, influential publications, and noteworthy journals within the neutrosophic domain. To achieve this, we have curated a dataset comprising scholarly papers retrieved from Clarivate Analytics’ Web of Science Core Collection database, employing keywords closely aligned with neutrosophic theory and its applications, spanning a specified timeframe starting from the year in which the first paper on neutrosophic theory was published, namely, from 2005 until 2022. Our findings underscore sustained and robust scholarly interest in neutrosophic theory, characterized by a considerable high annual growth rate of 43.74% during the specified period. Additionally, our investigation delves into the identification and analysis of pivotal keywords and emerging trends, shedding light on prominent research trajectories within this domain. Furthermore, we elucidate collaborative networks among authors, their academic affiliations, and the global distribution across diverse countries and territories, providing valuable insights into the worldwide proliferation of neutrosophic research and applications. Employing n-gram analysis techniques across titles, keywords, abstracts, and keyword-plus fields unveils a multitude of applications where neutrosophic theory plays a central role. The analysis culminates in a review of globally cited documents and a comprehensive discussion highlighting the significance of neutrosophic theory in contemporary research and problem-solving contexts.
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Ab.Rahim, Rosyawati, Taufik Ismail, Radhwa Abu Bakar, and Wan Azani Mustafa. "ARABIC VOCABULARY LEARNING THROUGH SMARTPHONE APPLICATION: A BIBLIOMETRIC ANALYSIS." International Journal of Modern Education 6, no. 22 (2024): 409–27. https://doi.org/10.35631/ijmoe.622029.

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In recent years, the integration of smartphones into language learning environments has gained significant attention due to its potential to enhance accessibility and effectiveness. This paper presents a bibliometric analysis focusing on the topic of "Arabic Vocabulary Learning Through Smartphone Application". The proliferation of smartphones and mobile applications has revolutionized various aspects of education, including language learning. Arabic language learning, in particular, has witnessed increased interest in leveraging smartphone applications to facilitate vocabulary acquisition. The lack of a systematic analysis of research on Arabic vocabulary learning through smartphone applications hampers the ability to identify emerging trends, key contributors, and high-impact studies in the field. This study employs bibliometric analysis techniques to examine the scholarly output related to Arabic vocabulary learning through smartphone applications. Data were retrieved from the Scopus database, focusing on publications from 2001 to 2023. Various bibliometric indicators, VosViewer version 1.16.20 tools to analyze publication trends, citation counts, co-authorship networks, and thematic analysis, were utilized to analyze the research landscape comprehensively. The analysis reveals a steady increase in publications over time, reflecting the growing interest and research activity in Arabic vocabulary learning through smartphone applications. This bibliometric analysis provides valuable insights into the trends, patterns, and impact of research on Arabic vocabulary learning through smartphone applications. The identified themes and high-impact articles contribute to our understanding of the field's development and offer directions for future research endeavors, educational practices, and policy decisions.
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Widyatami, Kania, and A. Sobandi. "Women's Leadership Research in Higher Education Institutions (HEIs): A Bibliometric Study." Manajemen dan Bisnis 24, no. 1 (2025): 181. https://doi.org/10.24123/mabis.v24i1.813.

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Gender disparity in leadership positions has been a topic of discussion for a considerable amount of time, including in the context of Higher Education Institutions (HEIs). This study applied bibliometric analysis to reveal how the field evolved. The data was retrieved from the Scopus database from 1952–2023 and processed using R software’s “bibliometrix” package and the Publish and Perish applications. A range of techniques comprising performance analysis and science mapping through co-citation analysis, bibliographic coupling, and co-word analysis were performed to uncover the intellectual, knowledge, and conceptual structures that give insights regarding the trends as well as the past, present, and future of the field.
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Lindahl, Jonas, and Rickard Danell. "The information value of early career productivity in mathematics: a ROC analysis of prediction errors in bibliometricly informed decision making." Scientometrics 109, no. 3 (2016): 2241–62. http://dx.doi.org/10.1007/s11192-016-2097-9.

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AbstractThe aim of this study was to provide a framework to evaluate bibliometric indicators as decision support tools from a decision making perspective and to examine the information value of early career publication rate as a predictor of future productivity. We used ROC analysis to evaluate a bibliometric indicator as a tool for binary decision making. The dataset consisted of 451 early career researchers in the mathematical sub-field of number theory. We investigated the effect of three different definitions of top performance groups—top 10, top 25, and top 50 %; the consequences of using different thresholds in the prediction models; and the added prediction value of information on early career research collaboration and publications in prestige journals. We conclude that early career performance productivity has an information value in all tested decision scenarios, but future performance is more predictable if the definition of a high performance group is more exclusive. Estimated optimal decision thresholds using the Youden index indicated that the top 10 % decision scenario should use 7 articles, the top 25 % scenario should use 7 articles, and the top 50 % should use 5 articles to minimize prediction errors. A comparative analysis between the decision thresholds provided by the Youden index which take consequences into consideration and a method commonly used in evaluative bibliometrics which do not take consequences into consideration when determining decision thresholds, indicated that differences are trivial for the top 25 and the 50 % groups. However, a statistically significant difference between the methods was found for the top 10 % group. Information on early career collaboration and publication strategies did not add any prediction value to the bibliometric indicator publication rate in any of the models. The key contributions of this research is the focus on consequences in terms of prediction errors and the notion of transforming uncertainty into risk when we are choosing decision thresholds in bibliometricly informed decision making. The significance of our results are discussed from the point of view of a science policy and management.
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Lundberg, Lars, and Håkan Grahn. "Research Trends, Enabling Technologies and Application Areas for Big Data." Algorithms 15, no. 8 (2022): 280. http://dx.doi.org/10.3390/a15080280.

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The availability of large amounts of data in combination with Big Data analytics has transformed many application domains. In this paper, we provide insights into how the area has developed in the last decade. First, we identify seven major application areas and six groups of important enabling technologies for Big Data applications and systems. Then, using bibliometrics and an extensive literature review of more than 80 papers, we identify the most important research trends in these areas. In addition, our bibliometric analysis also includes trends in different geographical regions. Our results indicate that manufacturing and agriculture or forestry are the two application areas with the fastest growth. Furthermore, our bibliometric study shows that deep learning and edge or fog computing are the enabling technologies increasing the most. We believe that the data presented in this paper provide a good overview of the current research trends in Big Data and that this kind of information is very useful when setting strategic agendas for Big Data research.
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Fahmi, Muhammad, Muhammad Andi Prayogi, Muhammad Taufik Lesmana, Maharani Citra Kencana, and Syahnita Syahnita. "Market Orientation Small Medium Enterprise: A Bibliometric Analysis of Publications between 1994 and 2023 Using VOSviewer Software." Proceeding International Pelita Bangsa 1, no. 01 (2023): 134–46. http://dx.doi.org/10.37366/pipb.v1i01.3113.

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This paper aims To analyze the most prolific and influential articles involved in market orientation research (MO) between 1994 to 2023. This Research paper uses bibliometric analysis techniques, quotations, and cocitations with Vosviewer software for investigated 766 publications in MO from 1994 to 2023 and uses the scopus.com database to visualize relevant articles and their results. Results of the analysis bibliometrics describe evolution research and interests scientific in market orientation over time. Study This gives more understanding _ of the focus of different studies and highlights contributor Main and Network collaboration in it. Second, literature about continued market orientation is growing and diversifying, focusing on understanding concepts and applications in the contemporary business world. While the novelty obtained from the study, This use approach bibliometric with VOSviewer and Scopus.com to analyze development literature about market orientation provides a holistic and in-depth view of relevant literature and provides a base for development understanding and application draft market orientation.
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