Study on the fusion of sports and medicine in China from 2012 to 2021: A bibliometric analysis via CiteSpace

Tu, Si-Jing; Jin, Chen; Chen, Bu-Tong; Xu, Anying; Luo, Chao; Wang, Xiaohe

doi:10.3389/fpubh.2022.939557

Cited by 14 publications

(18 citation statements)

References 9 publications

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“…The clustered network analysis functions to summarize the co‐occurring keywords by a scientific calculation method. The silhouette score above 0.7 is considered an efficient and convincing cluster 16 . There were 8 (silhouette score = 0.9111) and 11 (silhouette score = 0.8761) clusters produced by the log‐likelihood ratio in Chinese and English databases, respectively (Figure 5).…”

Section: Resultsmentioning

confidence: 96%

“…The silhouette score above 0.7 is considered an efficient and convincing cluster. 16 There were 8 (silhouette score = 0.9111) and 11 (silhouette score = 0.8761) clusters produced by the log‐likelihood ratio in Chinese and English databases, respectively (Figure 5 ). The clusters comprised keywords with different colors; the #0 cluster contained the largest number of keywords, and the overlap indicated the keyword belonged to more clusters simultaneously.…”

Section: Resultsmentioning

confidence: 97%

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Advances in stem cells treatment of diabetic wounds: A bibliometric analysis via CiteSpace

Ma,

Luo,

et al. 2024

Skin Research and Technology

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Diabetes is a chronic medical condition that may induce complications such as poor wound healing. Stem cell therapies have shown promise in treating diabetic wounds with pre‐clinical and clinical studies. However, little bibliometric analysis has been carried out on stem cells in the treatment of diabetic wounds. In this study, we retrieved relevant papers published from January 1, 2003, to December 31, 2023, from Chinese and English databases. CiteSpace software was used to analyze the authors, institutions, and keywords by standard bibliometric indicators. Our analysis findings indicated that publications on stem cells in the treatment of diabetic wounds kept increasing. The most prolific author was Qian Cai (n = 7) and Mohammad Bayat (n = 16) in Chinese and English databases, respectively. Institutions distribution analysis showed that Chinese institutions conducted most publications, and the most prolific institution was the Chinese People's Liberation Army General Hospital (n = 9) and Shahid Beheshti University of Medical Sciences (n = 17) in Chinese and English databases, respectively. The highest centrality keyword in Chinese and English databases was “wound healing” (0.54) and “in vitro” (0.13), respectively. There were 8 and 11 efficient and convincing keyword clusters produced by a log‐likelihood ratio in the Chinese and English databases, respectively. The strongest burst keyword was “exosome” (strength 3.57) and “endothelial progenitor cells” (strength 7.87) in the Chinese and English databases, respectively. These findings indicated a direction for future therapies and research on stem cells in the treatment of diabetic wounds.

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Section: Resultsmentioning

confidence: 96%

Section: Resultsmentioning

confidence: 97%

Advances in stem cells treatment of diabetic wounds: A bibliometric analysis via CiteSpace

Ma,

Luo,

et al. 2024

Skin Research and Technology

Self Cite

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“…CiteSpace software [ 15 ] was used to analyze information about co-authorship countries, institutions, co-cited references clusters, and keywords of strongest citation bursts. The centrality scores and keywords of citation bursts and heterogeneous networks were detected using CiteSpace software, which can help to visualize the research status, hot spots, and frontiers in a timely manner [ 16 ].…”

Section: Discussionmentioning

confidence: 99%

A Bibliometric Visualization Analysis on Vaccine Development of Coronavirus Disease 2019 (COVID-19)

et al. 2023

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Coronavirus disease 2019 (COVID-19), beginning in December 2019, has spread worldwide, leading to the death of millions. Owing to the absence of definitive treatment, vaccination against COVID-19 emerged as an effective strategy against the spread of the pandemic. Acceptance of the COVID-19 vaccine has advanced considerably, and vaccine-related research has significantly increased over the past three years. This study aimed to evaluate the content and external characteristics of COVID-19 vaccine-related literature for tracking research trends related to the global COVID-19 vaccine with the means of bibliometrics and visualization maps. A total of 18,285 records in 3499 journals were retrieved in the Web of Science Core Collection database and included in the final analysis. China was the first to focus on COVID-19 vaccine research, while European and American countries started late but developed rapidly. The USA and the UK are the top contributors to COVID-19 vaccine development, with the largest number of publications. The University of Washington and Harvard Medical School were the leading institutions, while Krammer, F. from Icahn School of Medicine at Mount Sinai was the author most active and influential to the topic. The New England Journal of Medicine had the highest number of citations and the highest TLS, and was the most cited and influential journal in the field of COVID-19 vaccine research. COVID-19 vaccine research topics and hotspots focused on populations’ attitudes towards vaccination, immunity-related information analysis of spike proteins, the effectiveness and side effects of the COVID-19 vaccine, and the public management of epidemic transmission. The findings of this study provide the global status, research hotspots and potential trends in the field of COVID-19 vaccine research, which will assist researchers in mastering the knowledge structure, and evaluating and guiding future developmental directions of COVID-19 vaccine

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“…By using network visualizations, researchers can quickly identify trends and outliers, and interactive data analysis can help them gain a deeper understanding of the data. Moreover, the paper employs CiteSpace (Tu et al, 2022), a bibliometric analysis tool developed by Professor Chaomei Chen with options for time slicing from 2002 to 2022, node types, and selection criteria based on the top 50 levels of the most cited or occurring items in each slice. Additionally, OriginPro improves and supplements the visual representation.…”

Section: Analytical Toolmentioning

confidence: 99%

An analysis and visualization of global wetlands based on scientmetric from 2002 to 2022

Chi,

Afandi,

Matthew

2023

Preprint

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Recent studies have focused on wetlands as they can benefit humans in terms of spiritual satisfaction and mental health. This paper evaluated the scientometric analysis of 2,388 studies published on the Web of Science between 2002 and 2022. It identified hotspots and trends in wetland research using VOS viewer, Origin, and Citespace software. Analyzing global wetland research publications shows a clear upward trend. Moreover, researchers in the United States, the People's Republic of China, Australia, Canada, and India devote considerable attention to wetland research. Network keyword co-occurrence analysis showed that wetland research covers constructed wetlands, climate change, wastewater treatment, phytoremediation, restoration, and hydrology. Furthermore, the United States is the world's main hotspot for wetland research; China, Canada, Australia, and others are behind. Due to the growing appreciation of wetlands' importance, wetland research will receive more attention from researchers around the globe. Additionally, wetland tourism articles should have improved quality since most publications are rarely cited. This paper presents an overview of the scientometric methodology for global wetlands research. Additionally, scholars working on wetlands can use scientometric analysis meaningfully and effectively for their future research.

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Study on the fusion of sports and medicine in China from 2012 to 2021: A bibliometric analysis via CiteSpace

Cited by 14 publications

References 9 publications

Advances in stem cells treatment of diabetic wounds: A bibliometric analysis via CiteSpace

Advances in stem cells treatment of diabetic wounds: A bibliometric analysis via CiteSpace

A Bibliometric Visualization Analysis on Vaccine Development of Coronavirus Disease 2019 (COVID-19)

An analysis and visualization of global wetlands based on scientmetric from 2002 to 2022

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