Mapping the Disciplinary Infrastructure: A Bibliometric Analysis of Games and Culture's Role in Game Studies Scholarship (2006–2025)

Gamification has emerged as an innovative pedagogical approach in foreign language learning, enhancing learner engagement, motivation, and outcomes. This study conducts a bibliometric analysis to map the intellectual structure and research landscape of gamification in this domain. Data were retrieved from the Scopus database using the keywords gamification, teaching, learning, and language, yielding 1,239 documents refined through OpenRefine for accuracy. Scopus Analyzer provided insights into publication output, sources, citations, and contributing countries, while VOSviewer visualized co-authorship, keyword co-occurrence, and citation networks. Findings indicate a steady growth in research between 2015 and 2025, with a marked surge after 2018 and a peak in 2024. Spain, the United States, Indonesia, and Malaysia are identified as leading contributors, representing both established and emerging research hubs. Keyword analysis revealed seven thematic clusters encompassing gamification, e-learning, motivation, and language acquisition, alongside emerging areas such as artificial intelligence, virtual reality, and digital storytelling. Highly cited studies focused on systematic reviews, Duolingo, and gamified tools like Kahoot. Overall, the study highlights gamification as a rapidly expanding, interdisciplinary field and provides an overview of key publication trends and thematic directions to inform future research and pedagogical practice in language education.

TikTok and young adults: A decade of research on mental health, cognition, sleep, and social outcomes (2016-2025).

Background: Colorectal cancer (CRC) ranks as the third most prevalent malignancy worldwide, yet early detection rates remain suboptimal. Diagnostic biomarkers hold significant promise for improving early CRC detection. This study conducts a bibliometric and visualization analysis to elucidate global research trends in diagnostic biomarkers for CRC. Methods: A dataset of 255 publications was extracted from the Web of Science Core Collection (WoSCC) spanning from 1 January 2014 to 10 September 2024. CiteSpace, VOSviewer, and Excel were employed for comprehensive analysis of authorship patterns, journal distribution, institutional contributions, geographic focus, keyword co-occurrence, and citation networks. Results: Publication volumes demonstrated an initial upward trajectory, peaking in 2021 before a slight decline. China emerged as the leading contributor, followed by Egypt, Iran, and the United States, with the Egyptian Knowledge Bank identified as the most prolific institution. Keyword analysis revealed concentrated research interests in Colorectal Cancer, Genetic Markers, Long Non-Coding RNAs (lncRNAs), Proteins, DNA Methylation, and MicroRNAs. Conclusion: Genomic, proteomic, and non-coding RNA biomarkers represent the primary research frontiers in CRC diagnostics. Future investigations should prioritize multi-institutional cohort studies and integrated multi-omics approaches to validate and refine biomarkers for clinical implementation in early CRC screening programs.

Amid global warming and urbanization, outdoor thermal comfort has become a critical consideration in landscape architecture. This study integrates a systematic review and bibliometric analysis of 1417 empirical studies (1980–2024) sourced from Web of Science, aiming to clarify the current state of research, identify core themes, and propose future directions. This study examines key evaluation models, the influence of spatial morphology, and their practical applications using keyword co-occurrence, citation networks, and thematic analyses. Findings show a significant rise in research over the past decade, particularly in tropical and subtropical regions. Core themes include thermal comfort indices (PMV, PET, and UTCI), microclimate regulation, and important spatial indicators (height-to-width ratio, sky view factor, and greening). The field is increasingly shifting towards simulation tools (such as ENVI-met and CFD) rather than traditional field measurements, with artificial intelligence emerging as a tool for predictive and regulatory purposes, though its application remains limited. However, much of the research focuses on small-scale morphological optimization and lacks a systematic framework for spatial representation. Future research should prioritize developing a comprehensive evaluation system adaptable to diverse landscapes, investigating the interplay between spatial form and thermal comfort, and advancing sustainable, low-carbon design strategies. The insights from this study provide a solid foundation for improving outdoor thermal comfort and guiding sustainable urban development through landscape architecture.

Data-driven trends in critical care informatics: a bibliometric analysis of global collaborations using the MIMIC database (2004-2024).

Drug-induced liver injury (DILI) has become one of the most common and serious adverse drug reactions owing to its high morbidity and leading cause of hepatic failures, which had attracted great attentions worldwide in the past two decades. A need therefore exists to conduct a bibliometric and visualized analysis of the global research trends on DILI with the aim of identifying the status of current research and prioritize the future research areas. Publications related to DILI from 1999 to 2019 were extracted through an electronic search of the Web of Science (WoS) and PubMed databases. VOSviewer software was used to perform visualized analysis of bibliographic coupling, co-authorship, co-citation and co-occurrence, and to assess the global trends. Totally of 6,563 publications were identified based on the inclusion criteria. It is noted that the global trends of literatures on DILI showed a significant increase over time and more importantly predict the relevant publications will rise continuously in the coming decades. The United States led in terms of publication numbers with the most citations (the highest H-index). Hepatology made great contributions to the highest H-index and the most citations of publications. University of North Carolina was regarded as the most contributive institution. Notably, after conducting co-occurrence and cluster analysis of keywords and citation networks, it is shown that the pathogenesis, clinical manifestations, diagnosis and risk factors of this field will become the most prominent research hotspots. The mapping results provides global development trends of publications on DILI from 1999 to 2019. Future studies focused on the diagnosis and predisposing factors of this field will be encouraged.

Introduction: The aim of this study is to reveal the research trends, focal points, and current status of maternal infections in the scientific literature through bibliometric analysis, identify knowledge gaps in the field, and provide guidance for future research. Pregnancy is a period when susceptibility to infections increases due to physiological changes and weakening of the immune system. In order to gain a general perspective on maternal infections, in this study, we aim to make a bibliometric analysis of the literature related to maternal infections and explore the research status, hotspots and frontiers in this field in recent 10 years. Methods: In this bibliometric study, the data were retrieved from the Web of Science Core Collection using the Title field search with the exact term “maternal infection”. Key parameters included citation counts, publication languages, journals, countries, and affiliations. The R-based Bibliometrix package and VOSviewer software (v1.6.18) were used for descriptive statistics and visualization of co-authorship, keyword co-occurrence, and citation networks. A total of 16,496 open-access articles from 1,952 sources, authored by 82,420 individuals, were analyzed. Results: All studies were published in science citation index expanded (SCIˇEXPANDED) and social sciences citation index (SSCI), as a result of the Web of Science. The publications have been published in 13 different sources (journals, books, letters etc.), mostly original articles (%82). The average citations per document was 31.19. The top active author was Romero R, the journal was Plos One with 846 articles, the affiliation was University of London, and the country was USA. Conclusion: This study systematically maps global research on maternal infections, in the last 20 years . The findings highlight trends, key contributors, and thematic shifts, emphasizing the need for future research on underrepresented areas and collaboration across countries and disciplines.

A bibliometric study and visualization analysis of ferroptosis-inducing cancer therapy

Purpose: The main purposes of this study were to analyze the document types and languages of published papers on coronavirus disease 2019 (COVID-19), along with the top authors, publications, countries, institutions, and disciplines, and to analyze the co-occurrence of keywords and bibliographic coupling of countries and sources of the most-cited COVID-19 literature.Methods: This study analyzed 16,384 COVID-19 studies published between December 2019 and June 2020. The data were extracted from the Web of Science database using four keywords: “COVID-19,” “coronavirus,” “2019-nCoV,” and “SARS-CoV-2.” The top 500 mostcited documents were analyzed for bibliographic and citation network visualization.Results: The studies were published in 19 different languages, and English (95.313%) was the most common. Of 157 research-producing countries, the United States (25.433%) was in the leading position. Wang Y (n=94) was the top author, and the <i>BMJ</i> (n=488) was the top source. The University of London (n=488) was the leading organization, and medicine-related papers (n=2,259) accounted for the highest proportion. The co-occurrence of keywords analysis identified “coronavirus,” “COVID-19,” “SARS-CoV-2,” “2019-nCoV,” and “pneumonia” as the most frequent words. The bibliographic coupling analysis of countries and sources showed the strongest collaborative links between China and the United States and between the <i>New England Journal of Medicine</i> and the <i>JAMA</i>.Conclusion: Collaboration between the United States and China was key in COVID-19 research during this period. Although BMJ was the leading title for COVID-19 articles, the co-author link between <i>New England Journal of Medicine</i> and <i>JAMA</i> was the strongest.

Rare diseases encompass over 7,000 conditions and affect an estimated 350–400 million individuals worldwide. Despite their prevalence, research remains limited. This study presents a bibliometric analysis of Quantum-Enhanced Neural Network (QENN)-based models for rare disease prediction. A dataset of 516 peer-reviewed articles retrieved from the Scopus database was analysed to map publication trends, citation networks, co-authorship linkages, keyword co-occurrence, and country-level contributions from inception to 2025. Results indicate a marked increase in publications over the past five years, driven by advances in quantum computing, bioinformatics, and artificial intelligence. Key research clusters were identified in quantum machine learning, biomedical prediction, and rare disease diagnostics. The findings provide a quantitative overview of the intellectual structure of this emerging interdisciplinary domain and highlight future directions for developing robust quantum-enhanced models in healthcare analytics.

BackgroundEndoscopy is the optimal method of diagnosing and treating early gastric cancer (EGC), and it is therefore important to keep up with the rapid development of endoscopic applications in EGC. This study utilized bibliometric analysis to describe the development, current research progress, hotspots, and emerging trends in this field.MethodsWe retrieved publications about endoscopic applications in EGC from 2012 to 2022 from Web of Science™ (Clarivate™, Philadelphia, PA, USA) Core Collection (WoSCC). We mainly used CiteSpace (version 6.1.R3) and VOSviewer (version 1.6.18) to perform the collaboration network analysis, co-cited analysis, co-occurrence analysis, cluster analysis, and burst detection.ResultsA total of 1,333 publications were included. Overall, both the number of publications and the average number of citations per document per year increased annually. Among the 52 countries/regions that were included, Japan contributed the most in terms of publications, citations, and H-index, followed by the Republic of Korea and China. The National Cancer Center, based in both Japan and the Republic of Korea, ranked first among institutions in terms of number of publications, citation impact, and the average number of citations. Yong Chan Lee was the most productive author, and Ichiro Oda had the highest citation impact. In terms of cited authors, Gotoda Takuji had both the highest citation impact and the highest centrality. Among journals, Surgical Endoscopy and Other Interventional Techniques had the most publications, and Gastric Cancer had the highest citation impact and H-index. Among all publications and cited references, a paper by Smyth E C et al., followed by one by Gotoda T et al., had the highest citation impact. Using keywords co-occurrence and cluster analysis, 1,652 author keywords were categorized into 26 clusters, and we then divided the clusters into six groups. The largest and newest clusters were endoscopic submucosal dissection and artificial intelligence (AI), respectively.ConclusionsOver the last decade, research into endoscopic applications in EGC has gradually increased. Japan and the Republic of Korea have contributed the most, but research in this field in China, from an initially low base, is developing at a striking speed. However, a lack of collaboration among countries, institutions, and authors, is common, and this should be addressed in future. The main focus of research in this field (i.e., the largest cluster) is endoscopic submucosal dissection, and the topic at the frontier (i.e., the newest cluster) is AI. Future research should focus on the application of AI in endoscopy, and its implications for the clinical diagnosis and treatment of EGC.

This study aims to reveal the fundamental structure of the academic literature on Central Bank Digital Currencies(CBDCs) by conducting a bibliometric analysis of the 343 publications. Using the keywords Central Bank Digital Currency and CBDC, studies published between 2018 and 2024 were obtained from the Web of Science database. The analysis and visualization processes were carried out using the VOSviewer. The findings indicate a remarkable increase in academic interest in CBDCs, with a concentration of publications originating from China, the United States, and European countries. Keyword co-occurrence and density analyses demonstrate that CBDCs constitute a multidisciplinary research domain that intersects not only with monetary innovation but also with areas such as blockchain, cybersecurity, data-privacy, and regulatory frameworks. Citation, author, and country network analyses reveal an increasingly integrated intellectual structure, a rise in international collaborations, and a deepening of research at a global scale. The study emphasizes the need to address CBDCs from technological, financial, and geopolitical perspectives. By highlighting thematic trends, conceptual gaps, and fundamental issues in the literature, it aims to provide a strategic perspective on the rise of digital currencies. This study seeks not only to contribute to academic discussions but also to benefit central banks, policymakers, market regulators and all relevant stakeholders.

Machine learning has become ubiquitous across all industries, including the relatively new application of predicting antimicrobial resistance. As the first bibliometric review in this field, we expect it to inspire further research in this area. The review employs standard bibliometric indicators such as article count, citation count, and the Hirsch index (H-index) to evaluate the relevance and impact of the leading countries, organizations, journals, and authors in this field. VOSviewer and Biblioshiny programs are utilized to analyze citation and co-citation networks, collaboration networks, keyword co-occurrence, and trend analysis. The United States has the highest contribution with 254 articles, accounting for over 37.57% of the total corpus, followed by China (103) and the United Kingdom (78). Among 58 publishers, the top four publishers account for 45% of the publications, with Elsevier leading with 15% of the publications, followed by Springer Nature (12%), MDPI, and Frontiers Media SA with 9% each. Frontiers in Microbiology is the most frequent publication source (33 articles), followed by Scientific Reports (29 articles), PLoS One (17 articles), and Antibiotics (16 articles). The study reveals a substantial increase in research and publications on the use of machine learning to predict antibiotic resistance. Recent research has focused on developing advanced machine learning algorithms that can accurately forecast antibiotic resistance, and a range of algorithms are now being used to address this issue.

Objective:Trabecular bone score (TBS) is a novel index for assessing bone microarchitecture quality. No bibliometric reviews to date have yet explored the literature of TBS. Therefore, this study aimed to provide a bibliometric review on the trends of research publications on TBS indexed in the Science Citation Index Expanded and the Social Sciences Citation Index from 2008 to 2019.Materials and Methods:Using the Science Citation Index Expanded and the Social Sciences Citation Index, articles designated as original articles or review articles were searched using the keyword “trabecular bone score.” The retrieved articles were analyzed using Histcite 12.03.17 and VOSviewer v. 1.6.15 to identify top authors, journals, countries, and occurrence of keywords.Results:A total of 430 original and review articles on TBS published between 2008 and 2019 were identified. The number of articles increased steadily from 2008 to 2019, reaching 80 articles in 2019 alone. The United States of America, Switzerland, and France were the countries with the highest output of publications. The journal Osteoporosis International published the largest number of articles on TBS. Analysis of co-occurrence of author-supplied keywords revealed four clusters, with TBS, bone mineral density, and osteoporosis as the most prominent keywords.Conclusion:This bibliometric study on TBS published between 2008 and 2019 revealed the collaborative network of countries and the highly published journals and authors. Co-occurrence of keywords also revealed clusters of research hotspots, which could contribute to the understanding of the current state of TBS research and the identification of research gap.

With the fast development of the digital world, the Internet of Things (IoT) has become an important element in the research domain nowadays. This research seeks to explore how the IoT literature developed from 2010 to 2026 via the bibliometric analysis of publications in Scopus databases. Using VOSviewer software to analyze co-authorship network, citation network, and keywords co-occurrence network, this study is intended to illustrate the structural features of the IoT literature in terms of its intellectural, social, and conceptual aspects. The findings indicate that IoT studies are characterized by close relations between researchers around the world, resulting in several major knowledge diffusion centers. In the context of citations analysis, the major sources not only contribute to technological development but also address issues like the sustainable environment, digital governance, and socio-economic transformations. As regards keywords co-occurrence analysis, the main groups of IoT research are smart environments, technology, engineering, and socio-technical studies. Overlay and density maps point out that there is a change in time concerning the focus of research towards more advanced concepts in the field, such as artificial intelligence in IoT, big data analysis, industry 4.0, and sustainable development. It can be concluded that IoT research is becoming more mature and multidisciplinary in nature, focusing more on addressing issues on a global scale. This paper will contribute to the existing literature on IoT research through a thorough systematic and long-term analysis of IoT studies.