A Case Study on Citation Network Analysis

In this chapter, the authors present a case study of Network Analysis in the field of bibliometrics, focused on the identification of central academic articles based on complex network metrics that can be implemented with algorithms covered throughout this book. The authors analyze a scientific citation network and systematically obtain the most central papers considering different perspectives of the selected document collection. Later, they discuss the potential benefits that the parallel kernels and the topology-aware partitioning algorithms can offer in the context of the presented study case. Finally, the authors summarize this book's main contributions and offer some concluding remarks.

2017 ◽  
Vol 14 (01) ◽  
pp. 1740005 ◽  
Author(s):  
Yasutomo Takano ◽  
Yuya Kajikawa ◽  
Makoto Ando

The detection of emerging technologies is vital for R&D managers and policymakers; hence, the bibliometric approach to analyzing papers and patents was developed. In this study, we proposed a new method, the research classification schema (RCS). We used citation network analysis to classify technologies into four categories: change-maker, breakthrough, matured, and incremental. Each technology is then plotted on the RCS based on its publication profile. A case study in the field of antennas was undertaken to evaluate the relevance and effectiveness of the RCS. The RCS method demonstrates the usefulness of the identification process of promising technologies, and therefore, the convenience of target designing research projects in universities and companies. We also discussed the effect of the resolution limit of clustering algorithms on the RCS to improve reliability.


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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