A Metric Approach to Hot Topics in Biomedicine via Keyword Co-occurrence
Categoría del artículo: Research Paper
Publicado en línea: 27 dic 2019
Páginas: 13 - 25
Recibido: 24 sept 2019
Aceptado: 24 nov 2019
DOI: https://doi.org/10.2478/jdis-2019-0018
Palabras clave
© 2019 Jane H. Qin, Jean J. Wang, Fred Y. Ye, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
Purpose
To reveal the research hotpots and relationship among three research hot topics in biomedicine, namely CRISPR, i PS (induced Pluripotent Stem) cell and Synthetic biology.
Design/methodology/approach
We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis.
Findings
The results reveal the main research hotspots in the three topics are different, but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other.
Research limitations
All analyses use keywords, without any other forms.
Practical implications
We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions, and for promoting biomedical developments.
Originality/value
We chose the core keywords in three research hot topics in biomedicine by using h-index.