Keyword Co-occurrence Network Analysis Research Articles

Identifying and Visualizing Global Research Trends and Hotspots of Artificial Intelligence in Medical Ultrasound: A Bibliometric Analysis.

Applications of artificial intelligence (AI) in medical ultrasound have rapidly grown in recent years. Therefore, it is necessary to identify and visualize global research trends and hotspots of AI in medical ultrasound to provide guidance for further exploitation. This study aims to highlight the global research trends and hotspots of the top 100 most-cited papers related to AI in medical ultrasound by combining quantitative and visualization methods. Articles on AI in medical ultrasound were selected from the WoSCC database and ranked by citation count. After identifying the 100 most-cited papers, we conducted a quantitative and visualized analysis of bibliometric characteristics, including leading research countries, prominent institutions, key authors and journals, author clusters and collaborations, and keyword co-occurrence network analysis. The top 100 highly cited papers from the WoSCC database were published between 1999 and 2021, with total citations ranging from 91 to 1580. The most cited article was published in IEEE Transactions on Medical Imaging. The top three most prolific countries/regions were the United States, mainland China, and the United Kingdom. The most published institutions and journals were Idaho University and IEEE Transactions on Medical Imaging. Twelve authors published more than four papers, with Suri, JS being the most productive author. The most studied topics were "ultrasound", "computer-aided diagnosis", and "segmentation". Ultrasonography of Superficial Organs was the main site that was studied the most. This study provides comprehensive insights into the characteristics of AI in medical ultrasound through quantitative and visualized analysis of the most highly cited literature. It serves as a valuable reference for the development and applications of AI, fostering potential collaborations within this domain.

The Research Development Track of Internet of Things in the Application Area of Communication Technology

Computer networks, mobile media, and information and communication technology (ICT) have grown progressively, and the development of communication technology is closely connected with that of ICT. This study explored the role played by the Internet of Things as ICT develops. Accordingly, through main path analysis and keyword co-occurrence network analysis, this study was designed to learn the major research development track, cluster status, and future research and development of the Internet of Things in the application area of communication technology.

A Review of Renewable Energy Investment in Belt and Road Initiative Countries: A Bibliometric Analysis Perspective

Since the proposal of the “Belt and Road” initiative (BRI) in 2013, China’s renewable energy investments in the countries along the route have shown rapid growth and diversification. These investments have shifted from initial product exports and engineering contracts to deeper equity investments and financing cooperation. They not only promote a global energy structure transformation towards green and low-carbon development but also bring significant economic growth and social progress to the participating countries. This study aims to systematically review the research status and trends of renewable energy investments in “Belt and Road” countries through comprehensive bibliometric analysis. Utilizing the Web of Science database and VOS viewer 1.6.17 software for visualization, this research reveals the publication trends, high-impact articles, institutional collaborations, and author networks in this field. Additionally, through keyword co-occurrence network analysis, three core research themes are identified: investment motivations, synergy effects, renewable energy consumption, and international cooperation. This systematic bibliometric analysis not only outlines the current research landscape but also provides important insights for identifying emerging research directions, thereby supporting more in-depth investigations into renewable energy investments within the “Belt and Road” initiative.

A bibliometric analysis of semantic segmentation in remote sensing images from 1981 to 2024

Semantic segmentation of remote sensing images plays a crucial role in various fields, such as disaster assessment, forestry measurement, and environmental monitoring. This study conducts a bibliometric analysis to investigate the research trends and development of semantic segmentation in remote sensing from 1981 to 2024. Utilizing the Web of Science Core Collection database, we retrieved representative literature data and analyzed the publication trends, main source journals, institutional cooperation, and keyword co-occurrence networks. The results show that the number of publications in this field has increased significantly since 2000, with an exponential growth pattern. Remote sensing is the most active research topic, followed by imaging science, photographic technology, and electrical and electronic engineering. The analysis of institutional cooperation reveals that Chinese research institutions, such as the Chinese Academy of Sciences and Wuhan University, play a leading role in this field and maintain close collaboration with research institutions worldwide. The keyword co-occurrence network analysis demonstrates the evolution of research focus from basic remote sensing and image processing techniques in the early stage to advanced image processing algorithms in the middle stage and deep learning and neural network technologies in the recent stage. The findings provide valuable insights into the current status and future trends of semantic segmentation in remote sensing, highlighting the importance of international cooperation and interdisciplinary exchange in driving technological innovation.

Unveiling Trends and Hotspots in Air Pollution Control: A Bibliometric Analysis

With the continuous acceleration of urbanization, air pollution has become an increasingly serious threat to public health. Strengthening the detection and control of pollutants has become a focal point in current society. In light of the increasing amount of literature in the field of air pollution control with every passing year, numerous reviews have been compiled; however, only a limited number employ bibliometric methods to comprehensively review and summarize research trends in this field. Herein, this study utilizes two bibliometric analysis tools, namely, CiteSpace (6.1.R6) and VOSviewer (1.6.20), to conduct a visual and comprehensive analysis of air pollution literature spanning 2000 to 2023. By doing so, it establishes a knowledge framework for research on air pollution control. Simultaneously, collaborative network analysis, reference co-citation network analysis, keyword co-occurrence network analysis, and keyword prominence are employed to undertake an exhaustive and profound visual examination within this domain. Results indicate that, over time, the number of relevant papers has exponentially increased, while interdisciplinary cooperation trends have gradually formed. Additionally, this study describes key areas of current research, including air pollution control residue treatment, regional joint air pollution control, and air pollution control mechanism analysis. Finally, challenges faced by researchers in this field and their different perspectives are discussed. To better integrate research findings on air pollution control, we explore the correlations among data and systematically present their developmental trends. This confirms the interdisciplinary nature of air pollution control research, in the hope of its guiding air pollution control in the future.

A Bibliometric investigation of leadership and technology integration in education: Trends and insights over three decades

In the context of Education 4.0 highlights the incorporation of digital technology into education. Effective leadership is crucial in guiding schools toward productive and long-term use of technology. Advanced information and communication technology has transformed the educational environment and encouraged researchers to develop leadership and technology integration in education. The purpose of this study is to provide an adequate overview of the academic environment by undertaking a thorough bibliometric analysis of leadership and technology integration in education. The findings of this research show the distribution of each type of publication and identify the core journals of the topic. This research also identified the United States and Malaysia as leading in contributions to the research topic. The citation trend, though not always aligning with publication peaks, underscores the importance of assessing both quantity and quality. Keyword analysis emphasizes the evolving focus on "digital leadership," reflecting current issues like COVID-19 and digital transformation’s impact on education. Keyword co-occurrence network analysis revealed clusters refer to the challenges of technology integration, roles of leadership, educational reform, organizational culture, administrative duties, crisis adaptation, and ethical digital behavior. The strategic diagram helps scholars understand changing trends in leadership and technology integration in education.

Scientometric Analysis and Visualization of Carbon Emission Studies in the Construction Industry

The field of carbon emissions in the construction industry has drawn extensive attention from researchers and practitioners due to the issue of global warming. In this study, an in-depth analysis of the research status, trends, and frontiers in the field of carbon emissions in the construction industry was carried out. The CiteSpace tool was used to visualize and analyze relevant papers from 1985 to 2023, to describe the overall knowledge structure in the field of carbon emissions in the construction industry using dual-map overlay analysis, journal co-citation network analysis, and keyword co-occurrence network analysis, to apply cluster analysis and burst detection to identify research trends in the field and the frontiers, and to analyze the scientific collaborations in the field. Further, the core issues in the field of carbon emissions in the construction industry were explored and relevant recommendations were proposed. The results are of great significance in identifying and analyzing knowledge systems and research patterns in the field of carbon emissions in the construction industry and help us to discover and understand the current deficiencies, trends, and frontiers in this field, thus providing useful suggestions and reflections for policymakers, practitioners, researchers, and other stakeholders.

Evolution of renewable energy laws and policies in China

This study employs Latent Dirichlet Allocation (LDA) topic modelling methodology to analyze documents related to renewable energy laws and policies at the central level in China. The objective is to investigate the development and evolution of renewable energy policies in China and to gain insights into the national-level attitudes towards renewable energy development. The study consists of two phases: initially, renewable energy policy documents undergo keyword analysis using word clouds and keyword co-occurrence network analysis to elucidate the focal areas and their interconnections within the legal and policy texts. Subsequently, after determining the optimal number of topics for modelling based on topic perplexity and consistency results, the text undergoes data cleaning to isolate words with practical significance. These words are then incorporated into the LDA topic model to analyze the distribution and content of potential topics within the policies. Lastly, by linearly segmenting the time frame, changes in topic intensity over time are visually examined using heat maps. The findings indicate that energy policies have consistently prioritized “development” and emphasized the significance of “new energy” in renewable energy policies. Moreover, as renewable energy has progressed, governments and policymakers have come to acknowledge the importance of comprehensive energy planning, transitioning to clean energy sources, and regulating the electricity market. This growing awareness has led to efforts to strengthen policy and regulatory measures to foster renewable energy's sustainable development and utilization. In summary, this study highlights the effectiveness of the LDA topic model in analyzing renewable energy policies, advancing its adoption and furthering research in the field.

Research status and challenges of Mycoplasma pneumoniae pneumonia in children: A bibliometric and visualization analysis from 2011 to 2023.

Mycoplasma pneumoniae (MP) infections occur in regional outbreaks every 3 to 7 years, lasting up to 2 years. Since this fall, there has been a significant rise in MP infections among children in China, indicating a regional epidemiological trend that imposes an increased national public health burden. To date, bibliometric methods have not been applied to studies on MP infection in children. We searched for all relevant English publications on MP pneumonia in children published from 2011 to 2023 using Web of Science. Analytical software tools such as Citespace and VOSviewer were employed to analyze the collected literature. 993 articles on MP pneumonia in children were published in 338 academic journals by 5062 authors affiliated with 1381 institutions across 75 countries/regions. China led in global productivity with 56.19%. Among the top 10 prolific organizations, 8 were Chinese institutions, with Soochow University being the most active, followed by Capital Medical University and Zhejiang University. Zhimin Chen from Zhejiang University School of Medicine exhibited the highest H-index of 32. Keyword co-occurrence network analysis revealed 7 highly relevant clusters. The current research hotspots and frontiers in this field are primarily MP pneumonia, refractory MP pneumonia, lactate dehydrogenase, asthma, and biomarker. We anticipate that this work will provide novel insights for advancing scientific exploration and the clinical application of MP pneumonia in children.

Scientometric analysis of quantum-inspired metaheuristic algorithms

Quantum algorithms, based on the principles of quantum mechanics, offer significant parallel processing capabilities with a wide range of applications. Nature-inspired stochastic optimization algorithms have long been a research hotspot. The fusion of quantum mechanics with optimization methods can potentially address NP-hard problems more efficiently and exponentially faster. The potential advantages provided by the ground-breaking paradigm have expedited the scientific output of quantum-inspired optimization algorithms locale. Consequently, a pertinent investigation is required to explain how ground-breaking scientific advancements have evolved. The scientometric approach utilizes quantitative and qualitative techniques to analyze research publications to evaluate the structure of scientific knowledge. Henceforth, the current research presents a scientometric and systematic analysis of quantum-inspired metaheuristic algorithms (QiMs) literature from the Scopus database since its inception. The scientometric implications of the article offer a detailed exploration of the publication patterns, keyword co-occurrence network analysis, author co-citation analysis and country collaboration analysis corresponding to each opted category of QiMs. The analysis reveals that QiMs solely account to 26.66% of publication share in quantum computing and have experienced an impressive 42.59% growth rate in the past decade. Notably, power management, adiabatic quantum computation, and vehicle routing are prominent emerging application areas. An extensive systematic literature analysis identifies key insights and research gaps in the QiMs knowledge domain. Overall, the findings of the current article provide scientific cues to researchers and the academic fraternity for identifying the intellectual landscape and latest research trends of QiMs, thereby fostering innovation and informed decision-making.

Analysing trends and patterns in retrenchment research: a bibliometric approach

In today’s highly competitive business market, the optimization of operational efficiency and expense reduction is crucial for firms to maintain profitability and ensure long-term sustainability. A popular corporate strategy for achieving such goals is retrenchment, which involves shrinking or reorganizing organizational activities. The significance of conducting a bibliometric study on retrenchment lies in its ability to offer valuable insights to scholars, policymakers, and stakeholders interested in retrenchment and implementation and how it impacts employees and organisations. The review further identifies trends and patterns in retrenchment, highlighting significant works, and presenting a comprehensive understanding of it as a corporate strategy. To evaluate the research on labour retrenchment, a document search was conducted using article titles and keywords, analysing published documents and their citations. The data on publications were obtained from the Scopus database for this study. The VOS viewer tool was utilized to visualize the data derived from Scopus, while Harzing’s Publish or Perish programme (Windows GUI Edition) was employed to analyse the citations and performance indicators of the publications. The findings reveal a total of 79 documents published by 177 writers between 1982 and 2023. There is evidence that the sum of publications on retrenchment has been steadily snowballing over time necessitating attention. The study observed a global interest in retrenchment research, with contributions from various countries and across multiple subject areas. The study also examined the top 26 most cited publications on retrenchment, showing variations in citation numbers and rates over time. Keyword co-occurrence network analysis identified significant groupings in retrenchment research. These clusters offer a comprehensive view of retrenchment research which adequately covers a range of themes, including the healthcare industry in the United States, the intersection of retrenchment and healthcare, the psychological effects, economic factors, and ethical implications.

대학 학생성공 해외 연구동향 분석: 상세 서지정보 분석

The purpose of this study was to examine international research trends with respect to student success in the field of higher education. In order to address the study’s purpose, we collected scholarly articles that addressed issues and topics concerning student success published between 1974 and 2023. This study employed bibliometric analysis targeted towards bibliometric information of a total of 615 articles housed in SSCI- and Scopus-indexed journals. The information was extracted from the Web of Science, a web database powered by Clarivate Analytics. For data analysis, we utilized the bibliometrix package in RStudio. The study’s findings show that the quantity of articles on student success has increased since the late 2000s, especially surging since the mid-2010s. The majority of these investigations were conducted in Western countries, predominantly the United States, and international collaboration was scarce. Through the frequency analysis of co-citation data, author, and key terms, it was revealed that the foundational underpinnings of student success have been rooted in the concepts of student retention and student engagement. According to the results of keyword co-occurrence network analysis, we categorized sub-themes into five clusters: (a) teaching and learning assessments within online environments, (b) institutional support and empirical approaches for student retention, (c) psychological and emotional aspects responding to student crisis, (d) student engagement and experience-based student-oriented perspectives, and (e) associations with adult education and career development in community colleges. Finally, the study’s findings from thematic analysis demonstrate that research on student success has emerged based on inter- and intra-collaborations within and across various domains of studies. Based on the findings, academic and practical implications are suggested for research and practice in South Korea’s higher education context.

The Study of Trends in AI Applications for Vehicle Maintenance Through Keyword Co-occurrence Network Analysis

The increasing complexity of a vehicle's digital architecture has created new opportunities to revolutionize the maintenance paradigm. The Artificial Intelligence (AI) assisted maintenance system is a promising solution to enhance efficiency and reduce costs. This review paper studies the research trends in AI-assisted vehicle maintenance via keyword co-occurrence network (KCN) analysis. The KCN methodology is applied to systematically analyze the keywords extracted from 3153 peer-reviewed papers published between 2011 and 2022. The network metrics and trend analysis uncovered important knowledge components and structure of the research field covering AI applications for vehicle maintenance. The emerging and declining research trends in AI models and vehicle maintenance application scenarios were identified through trend visualizations. In summary, this review paper provides a comprehensive high-level overview of AI-assisted vehicle maintenance. It serves as a valuable resource for researchers and practitioners in the automotive industry. This paper also highlights potential research opportunities, limitations, and challenges related to AI-assisted vehicle maintenance.

BIBLIOMETRICS OF CALCIUM PHOSPHATE UTILISATION IN DENTISTRY

Calcium phosphates (CaPs) are frequently implemented in bone tissue engineering, especially in orthopaedics and dentistry, due to the resemblance of their inorganic constituent with bone or dental tissue. They have excellent biocompatibility, osseointegration and osteoconduction properties. The compounds are also widely available in nature and biological systems. Despite their excellent properties, various mechanical and physical factors affect their cell adhesion, proliferation, and bioactivity. Different applications have been highlighted such as synthesis techniques, coatings and composite scaffolds to utilise the bioactive characteristics of CaP in tissue engineering. A systemic data search was initiated using the “Article title, Abstract, and Keywords” search category of Scopus database to retrieve the original articles published in this field. With the aid of Scopus database and VOS Viewer software, the most contributing authors, countries, institution were retrieved. The most cited publication, publication year, and keyword co-occurrence network analysis facilitate the significant research focus and trends. This bibliometrics approach aims to quantify and analytically evaluate the research efficiency contributed in this specific area to the scientific community and reviews the substantial research trends of calcium phosphate application in dentistry.

A Bibliometric Analysis of the Literature on Food Industry Supply Chain Resilience: Investigating Key Contributors and Global Trends

Purpose: In light of ongoing challenges such as climate change, pandemics, and globalization, it is critical to have resilient food industry supply chains that can operate effectively in uncertain conditions. This study aims to contribute to this effort by investigating current trends and developments in the area of food industry supply chain resilience and identifying potential areas for improvement. Design/methodology/approach: We conducted a comprehensive bibliometric analysis of 122 articles published between 2008 and 2023, utilizing multiple quantitative measures such as bibliographic coupling and keyword co-occurrence network analysis. Findings: Our study identifies five distinct clusters of research on food industry supply chain resilience. We found that food systems resilience and public health is the most extensively studied aspect, indicating the importance of ensuring that our food supply chains are capable of withstanding disruptions to maintain public health. The other four clusters–seafood supply chain resilience and risk management; digital and sustainable food systems; agri-food Industry 4.0 and sustainability; and meat production and the food industry–each represent important areas for future research and development. Originality: To our knowledge, this is the first study that uses a bibliometric approach to analyze the resilience of food supply chain systems. By doing so, we provide a unique and original contribution to the existing literature on food supply chain systems, as prior bibliometric analyses have not specifically focused on the resilience aspect. Practical implications: Our findings highlight the need for continued research and development in the area of food industry supply chain resilience. By identifying the most pressing areas for improvement and future research, our study can help inform policy decisions and guide industry efforts to create more resilient food supply chains that can adapt to changing conditions.

Global research trends and focus on the link between colorectal cancer and gut flora: a bibliometric analysis from 2001 to 2021.

Colorectal cancer (CRC) is a highly prevalent cancer, and the global healthcare system bears a significant burden due to its incidence. Modulating the gut microbiota is a promising approach to enhance the efficacy of CRC treatment and reduce its adverse effects. The causal relationship between specific microorganisms' presence and CRC development has been widely validated. However, few studies have investigated this relationship using bibliometric methods. Therefore, this study analyzed the research hotspots and trends in human gut microbiology and CRC over the last two decades from a bibliometric perspective. The study aims to provide novel insights into basic and clinical research in this field. The articles and reviews on gut microbiota in CRC were obtained from the Web of Science Core Collection (WOSCC) on November 2, 2022. CiteSpace and VOSviewer were used to conduct the bibliometric and knowledge-map analysis. A total of 2,707 publications were obtained, with a rapid increase in the number of publications since 2015. The United States and China are the main contributors in this field and have established a network of partnerships in several countries. 414 academic journals have published articles on this topic. The author with the highest number of publications is Jun Yu from the Chinese University of Hong Kong. In addition to "intestinal flora" and "colorectal cancer," high frequency terms in the keyword co-occurrence network analysis included inflammatory bowel disease, Fusobacterium nucleatum, inflammation, long-chain fatty acids, ulcerative colitis, bile acids, and resistant starch. Analysis of keyword trends using burst testing revealed that biomarkers, abnormal crypt foci, bifidobacteria, β-glucuronidase, short-chain fatty acids, bile acids, and DNA methylation are at the forefront of research in this area. The findings of this study provide a bibliometric analysis and visualization of the key research areas in gut microbiota and CRC over the past 20 years. The results suggest that the role of gut microbiota in CRC and its underlying mechanisms should be closely monitored, particularly in the areas of biomarkers, metabolic pathways, and DNA methylation, which may emerge as hot topics in this field.

Research Progress and Hotspot of Information Retrieval Correlation based on CiteSpace

Taking 1760 journal papers of information retrieval relevance in the core database of Web of Science as the research object, using literature co-citation network and keyword co-occurrence network analysis, with information visualization as the means, this paper summarizes the research on the relevance of information retrieval. It is found that the current information retrieval correlation research network is concentrated, which is mainly divided into two main knowledge groups, retrieval algorithm and correlation cognition, with few frontier branches. And the knowledge fusion between the two groups needs to be strengthened. Since the emergence of natural language processing, information retrieval relevance has been improved along the path of natural language processing-machine learning-deep learning.

Global research status and trends in orthopaedic surgical robotics: a bibliometric and visualisation analysis study.

This study aimed to investigate and summarise the current state of research and trends in orthopaedic surgical robots. Data on publicly available publications related to orthopaedic surgical robots were extracted by abstract searches of the Web of Science Core Collection database. A bibliometric analysis and detailed reading of the publications were then carried out and the information was visualised using co-authorship analysis, coupling analysis, co-citation analysis and co-occurrence analysis in VOSviewer. With 436 publications included in the study from 1993 to 2022, the overall contribution of publications to the world showed an increasing trend year by year, with a particularly pronounced after 2017, and a geographical trend of predominantly East Asia, North America, and Western Europe. Of these, China was the largest contributor (n = 128). Overall, the UK affiliates and their scholars were leaders in the field, with a high number of publications, total citations, average citations per article and H-index. The most published institutions and authors were Imperial College London (n = 21) and Professor Fares Sahi Haddad of University College London (n = 12), respectively. Journals with a high overall impact on robotic orthopaedic surgery were the Journal of Arthroplasty, Bone Joint Journal, International Journal of Medical Robotics and Computer Assisted Surgery. Keyword co-occurrence network analysis revealed four main clusters: robot-assisted knee, hip arthroplasty, spine surgery, and robotic technology research and development. The top three most common sites for robot-assisted surgery use were the knee, hip and spine. The most used robot types were the knee and spine, with Mako and Arobot being the most used robots for the knee and TiRobot for the spine. This study comprehensively reveals the current status and trends of global research on orthopaedic surgical robots, covering countries, institutions, authors, journals, research hotspots, robot types and surgical sites, providing directional guidance and research ideas for further research on the technological development and clinical evaluation of orthopaedic surgical robots.

Grassland Ecosystem Progress: A Review and Bibliometric Analysis Based on Research Publication over the Last Three Decades

Understanding the grassland ecosystem is crucial for improving grassland ecosystem functions and services such as climate regulation, water and soil conservation, carbon sequestration, and biodiversity and gene pool maintenance. However, a systematic and comprehensive review of the relevant literature is still unclear and lacking. The VOSviewer software and cluster analysis were used to visually analyze and perform dimension reduction classification on the 27,778 studies related to grassland ecosystem research based on the Web of Science database. The number of publications targeting grassland ecosystem increased rapidly from 2006 to 2021. Ecology, agronomy, and environmental science were the most popular research categories, and the top journal sources were Remote Sensing, Journal of Ecology, and Ecology and Evolution. The leading publishing countries were the United States, China, and Germany. The top three institutions were the Chinese Academy of Sciences, the University of Chinese Academy of Sciences, and Colorado State University. Cooperation between different countries and institutions had increased. Keyword co-occurrence network analysis showed that Biodiversity, Vegetation and Conservation were the most popular study areas, grassland management, climate change, land use pattern, and ecosystem impact were the hot research topics. All studies could be divided into three categories by cluster analysis: grassland ecological characteristics including basic physicochemical properties, vegetation community characteristics, aboveground and belowground biomass, and soil structural quality of grassland; driving mechanisms that demonstrated effects of human activities and climate change on grassland ecosystem function; and grassland ecosystem services that focused the influences of different grassland management strategies on ecological services, animal welfare and human well-being. The three topic categories of reviewed studies were interrelated and consistent with each other, and the performances were progressive. This paper reviewed the trend evolution through keyword hotspots and analyzed the future research directions to provide an important reference for scientists to better respond to the balance of herbage and sustainable utilization of grassland and maintenance of ecological security.

Top 100 most-cited articles on renal cell carcinoma: A bibliometric analysis.

To analyze the top 100 most-cited articles on renal cell carcinoma (RCC) using bibliometric methods based on the Web of Science core collection database and to explore the research status, hotspots, and emerging trends in RCC. The literature on RCC was searched in the Web of Science core collection database using a specific search strategy, and the types of literature were limited to articles and reviews, with no restrictions to language and publication date. The top 100 articles with the highest number of citations were extracted after the manual screening. The publication year, the number of citations, authors, country, institution, journal, and keywords of these articles were collected and analyzed. Descriptive statistics and visual analysis were performed using Microsoft Excel, VOSviewer, CiteSpace, R, and SPSS. The number of citations of the top 100 articles varied from 541 to 4530, with a median citation count of 807.5, and the citation rates ranged from 13.8 to 448.4 citations per year. Motzer RJ (n = 22), Escudier B (n = 13), Rini BI (n = 13), and Hutson TE (n = 11) were major contributors to this research area, with Motzer RJ publishing 16 articles as the first author. The US (n = 73), France (n = 5), Canada (n = 4), and Sweden (n = 4) were the leading countries for RCC studies. MEMORIAL SLOAN KETTERING CANCER CENTER (n = 22) was the institution with the highest number of publications. These 100 articles were derived from 24 journals, and the New England Journal of Medicine had the largest number of articles published (n = 18, impact factor = 91.245). The keyword co-occurrence network analysis showed that research hotspots in this field included molecular mechanisms of RCC development and progression, surgical treatment, targeted drug-related clinical trials, and immunotherapy. We analyzed the top 100 articles with the highest number of citations in the field of RCC and identified the influential authors, countries, institutions, and journals in this field. This study also presented the current research status, hotspots, and future trends in RCC.