Technological barriers and research trends in fuel cell technologies: A citation network analysis

2014 ◽  
Vol 82 ◽  
pp. 66-79 ◽  
Author(s):  
Jonathan C. Ho ◽  
Ewe-Chai Saw ◽  
Louis Y.Y. Lu ◽  
John S. Liu
Keyword(s):  
Fuel Cell ◽  
Network Analysis ◽  
Citation Network ◽  
Research Trends ◽  
Cell Technologies ◽  
Citation Network Analysis ◽  
Technological Barriers

Longitudinal Analysis of Mechanism and Machine Theory: Geospatial Productivity, Journal Citation Networks, and Researcher Communities

2016 ◽  
Vol 138 (3) ◽  
Author(s):  
Dar-Zen Chen ◽  
Ya-Yun Lee
Keyword(s):  
Network Analysis ◽  
Longitudinal Analysis ◽  
Citation Network ◽  
The United States ◽  
Research Trends ◽  
Citation Networks ◽  
The Past ◽  
Research Communities ◽  
Citation Network Analysis ◽  
Machine Theory

This paper presents a longitudinal analysis through bibliometrics from three perspectives: geospatial analysis of research productivity, citation network analysis of journals, and top productive researchers with research communities. The purpose of these analyses is to detect the development and research trends of mechanism and machine theory (MMT) field. The results indicate that the productivity of MMT publications shows a growing trend. The United States (U.S.) has dominated MMT publications, but its ratio has dropped off approximately twenty percent in the past three decades, while China (CN) has rapidly grown in its quantity and ratio of MMT publications. The concentration of MMT publications among various countries has declined over time. Through citation network analysis, the relationships between journals in the MMT field are identified and their variations over periods are derived. The citations have been centered between five related journals and three core journals. Additionally, the evolution of research communities corresponding to the top 30 productive researchers and the distribution of the publications in each community among countries are identified.

scholarly journals Study on Horizon Scanning by Citation Network Analysis and Text Mining: A Focus on Drug Development Related to T Cell Immune Response

2021 ◽  
Author(s):  
Erika Fujii ◽  
Takuya Takata ◽  
Hiroko Yamano ◽  
Masashi Honma ◽  
Masafumi Shimokawa ◽  
...  
Keyword(s):  
Network Analysis ◽  
Text Mining ◽  
Product Development ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Citation Network ◽  
Research Trends ◽  
Horizon Scanning ◽  
Scientific Papers ◽  
Citation Network Analysis

AbstractCertain innovative technologies applied to medical product development require novel evaluation approaches and/or regulations. Horizon scanning for such technologies will help regulators prepare, allowing earlier access to the product for patients and an improved benefit/risk ratio. This study investigates whether citation network analysis and text mining of scientific papers could be a tool for horizon scanning in the field of immunology, which has developed over a long period, and attempts to grasp the latest research trends. As the result of the analysis, the academic landscape of the immunology field was identified by classifying 90,450 papers (obtained from PubMED) containing the keyword “immune* and t lymph*” into 38 clusters. The clustering was indicative of the research landscape of the immunology field. To confirm this, immune checkpoint inhibitors were used as a retrospective test topic of therapeutics with new mechanisms of action. Retrospective clustering around immune checkpoint inhibitors was found, supporting this approach. The analysis of the research trends over the last 3 to 5 years in this field revealed several candidate topics, including ARID1A gene mutation, CD300e, and tissue resident memory T cells, which shows notable progress and should be monitored for future possible product development. Our results have demonstrated the possibility that citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of life science fields such as immunology.

scholarly journals A Systematic Literature Network Analysis of Existing Themes and Emerging Research Trends in Circular Economy

2020 ◽  
Vol 12 (4) ◽  
pp. 1633 ◽  
Author(s):  
Fatima Khitous ◽  
Fernanda Strozzi ◽  
Andrea Urbinati ◽  
Fernando Alberti
Keyword(s):  
Network Analysis ◽  
Circular Economy ◽  
Citation Network ◽  
Research Trends ◽  
Future Research ◽  
Citation Score ◽  
Theoretical Perspectives ◽  
Citation Network Analysis ◽  
Research Domains ◽  
Over Time

The debate about Circular Economy (CE) has been increasingly enriched by academics through a vast array of contributions, based on several theoretical perspectives and emanating from several research domains. However, current research still falls short of providing a holistic and broader view of CE, one that combines existing themes and emerging research trends. Accordingly, based on a Systematic Literature Network Analysis, this paper tackles this gap. First, a Citation Network Analysis is used to unearth the development of the CE literature based on papers’ references, whilst the Main Path is traced to detect the seminal papers in the field through time. Second, to consider the literature in its broader extent, a Keywords Co-Occurrence Network Analysis is conducted based on papers’ keywords, whereby all papers in the dataset, including the non-cited papers, are assessed. Additionally, a Global Citation Score analysis is conducted to uncover the recent breakthrough research, in addition to the Burst Analysis used to detect the dynamic development of CE literature over time. By doing so, the paper explores the development of the CE body of knowledge, reveals its dynamic evolution over time, detects its main theoretical perspectives and research domains, and highlights its emerging topics. Our findings unfold the evidence of eight main trends of research about CE, unearth the path through which the CE concept emerged and has been growing, and concludes with promising avenues for future research.

Textile-based fiber optic sensors for health monitoring: A systematic and citation network analysis review

2021 ◽  
pp. 004051752110362
Author(s):  
Ka-Po Lee ◽  
Joanne Yip ◽  
Kit-Lun Yick ◽  
Chao Lu ◽  
Chris K Lo
Keyword(s):  
Network Analysis ◽  
Fiber Optic ◽  
Vital Signs ◽  
Citation Network ◽  
Fiber Optic Sensors ◽  
Superior Performance ◽  
Vital Signs Monitoring ◽  
Wear Comfort ◽  
Citation Network Analysis ◽  
Research Domains

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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