Ranking Scientific Articles in a Dynamically Evolving Citation Network

Author(s):  
Xiaorui Jiang ◽  
Chenhui Gao ◽  
Ronghua Liang
Keyword(s):  
2020 ◽  
Vol 13 ◽  
Author(s):  
Gaurav Gaurav ◽  
Abhay Sharma ◽  
G S Dangayach ◽  
M L Meena

Background: Minimum quantity lubrication (MQL) is one of the most promising machining techniques that can yield a reduction in consumption of cutting fluid more than 90 % while ensuring the surface quality and tool life. The significance of the MQL in machining makes it imperative to consolidate and analyse the current direction and status of research in MQL. Objective: This study aims to assess global research publication trends and hot topics in the field of MQL among machining process. The bibliometric and descriptive analysis are the tools that the investigation aims to use for the data analysis of related literature collected from Scopus databases. Methods: Various performance parameters are extracted, such as document types and languages of publication, annual scientific production, total documents, total citations, and citations per article. The top 20 of the most relevant and productive sources, authors, affiliations, countries, word cloud, and word dynamics are assessed. The graphical visualisation of the bibliometric data is presented in terms of bibliographic coupling, citation, and co-citation network. Results: The investigation reveals that the International Journal of Machine Tools and Manufacture (2611 citations, 31 hindex) is the most productive journal that publishes on MQL. The most productive institution is the University of Michigan (32 publications), the most cited country is Germany (1879 citations), and the most productive country in MQL is China (124 publications). The study shows that ‘Cryogenic Machining’, ‘Sustainable Machining’, ‘Sustainability’, ‘Nanofluid’ and ‘Titanium alloy’ are the most recent keywords and indications of the hot topics and future research directions in the MQL field. Conclusion: The analysis finds that MQL is progressing in publications and the emerging with issues that are strongly associated with the research. This study is expected to help the researchers to find the most current research areas through the author’s keywords and future research directions in MQL and thereby expand their research interests.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Raul Rodriguez-Esteban

Abstract Background Numerous efforts have been poured into annotating the wealth of knowledge contained in biomedical articles. Thanks to such efforts, it is now possible to quantitatively explore relations between these annotations and the citation network at large scale. Results With the aid of several large and small annotation databases, this study shows that articles share annotations with their citation neighborhood to the point that the neighborhood’s most common annotations are likely to be those appearing in the article. Conclusions These findings posit that an article’s citation neighborhood defines to a large extent the article’s annotated content. Thus, citations should be considered as a foundation for future knowledge management and annotation of biomedical articles.


AI & Society ◽  
2021 ◽  
Author(s):  
Milad Mirbabaie ◽  
Lennart Hofeditz ◽  
Nicholas R. J. Frick ◽  
Stefan Stieglitz

AbstractThe application of artificial intelligence (AI) in hospitals yields many advantages but also confronts healthcare with ethical questions and challenges. While various disciplines have conducted specific research on the ethical considerations of AI in hospitals, the literature still requires a holistic overview. By conducting a systematic discourse approach highlighted by expert interviews with healthcare specialists, we identified the status quo of interdisciplinary research in academia on ethical considerations and dimensions of AI in hospitals. We found 15 fundamental manuscripts by constructing a citation network for the ethical discourse, and we extracted actionable principles and their relationships. We provide an agenda to guide academia, framed under the principles of biomedical ethics. We provide an understanding of the current ethical discourse of AI in clinical environments, identify where further research is pressingly needed, and discuss additional research questions that should be addressed. We also guide practitioners to acknowledge AI-related benefits in hospitals and to understand the related ethical concerns.


2021 ◽  
pp. 004051752110362
Author(s):  
Ka-Po Lee ◽  
Joanne Yip ◽  
Kit-Lun Yick ◽  
Chao Lu ◽  
Chris K Lo

Receptivity towards textile-based fiber optic sensors that are used to monitor physical health is increasing as they have good flexibility, are light in weight, provide wear comfort, have electromagnetic immunity, and are electrically safe. Their superior performance has facilitated their use for obtaining close to body measurements. However, there are many related studies in the literature, so it is challenging to identify the knowledge structure and research trends. Therefore, this article aims to provide an objective and systematic literature review on textile-based fiber optic sensors that are used for monitoring health issues and to analyze their trends through a citation network analysis. A full-text search of journal articles was conducted in the Web of Science Core Collection, and a total of 625 studies was found, with 47 that were used as the sample. Also, CitNetExplorer was used for analyzing the research domains and trends. Three research domains were identified, among them, “Flexible sensors for vital signs monitoring” is the largest research cluster, and most of the articles in this cluster focus on respiratory monitoring. Therefore, this area of study should probably be on the academic radar. The collection of data on textile-based fiber optic sensors is invaluable for evaluating degree of rehabilitation, detecting diseases, preventing accidents, as well as gauging the performance and training successfulness of athletes.


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