Intellectual structure of knowledge in iMetrics: A co-word analysis

2017 ◽  
Vol 53 (3) ◽  
pp. 705-720 ◽  
Author(s):  
Ali Akbar Khasseh ◽  
Faramarz Soheili ◽  
Hadi Sharif Moghaddam ◽  
Afshin Mousavi Chelak
Author(s):  
Fatemeh Makkizadeh ◽  
Esmaeil Bigdeloo

Background: The Co-word analysis has the ability to identify the intellectual structure of knowledge in a research domain and reveal its subsurface research aspects. Objective: This study examines the intellectual structure of knowledge in the field of Andrology during the period 2008-2017 using Co-word analysis. Materials and Methods: In this descriptive-analytical study with a scientometric approach, the WoS database was searched for papers indexed under “Andrology” over the period 2008–2017. The data were analyzed using Co-word, clustering methods, and strategic diagram with the help of SPSS, UcInet, RavarPreMap and VOSviewer software. Results: The highest publication rate in the area of Andrology was seen in countries like the USA, China, Italy, and Iran. The top three journals that published papers on the field were Fertility and Sterility, Andrologia, Human reproduction. The results showed that the keyword “Spermatozoa” and two pairs of frequently used keywords, namely “Azoospermia * Oligospermia” were the most frequent in the field of Andrology. The results of hierarchical clustering led to 13 clusters. The clusters “Reproductive Techniques” and “Spermatogenesis” are the core clusters and play an effective role. The ”Post-Testicular causes” and “Neoplasm” clusters are in marginal. Conclusion: This study represented that Co-word analysis can well illustrate the intellectual structure of an area. Considering the frequency of keywords along with the clusters obtained, it seems that the majority of research approach was seen on infertility treatments, especially through assisted reproductive technology. Despite the importance of psychological aspects as well as education of reproductive health, these subjects have not been sufficiently considered.


2016 ◽  
Vol 107 (2) ◽  
pp. 497 ◽  
Author(s):  
Karmen Stopar

<p><span style="font-family: Times New Roman; font-size: medium;">Increasing number of scientific publications points to quick developments in the field of nanoscience and nanotechnology. Nanotechnology offers potentials of unimaginable proportions. Innovative possibilities present themselves in many areas of human activity, including agriculture, for example in precision farming, reduction of pollution and increasing crop yields. We bibliometrically assessed interactions between nanotechnology and agriculture. With co-word analysis in particular, we examined aspects of agro-nano applications related to plant protection. In order to analyze and map the structure of knowledge, we employed selected terms from a general citation database Web of Science (WOS) as well as specialized bibliographic database CAB Abstracts which covers life sciences with a special emphasis on agriculture. Our thematic maps (visualization) present some principal themes and relations among them. Pesticides, biosensors and detection are the main keywords in the network of words from article titles and network of the KeyWords+. Analysis of controlled terms (descriptors, classification codes) from CAB Abstracts in connection with pesticides shows two important directions of research: pollution and environmental topics, and topics related to human health, experimental animals and related. </span></p><p> </p>


2021 ◽  
Vol 7 (1) ◽  
pp. 283-292
Author(s):  
Rosaura Fernández-Pascual ◽  
Ana Marín Jiménez ◽  
María Pilar Fernández- Sánchez

This paper explores how to incorporate information visualization tools into qualitative studies to represent the underlying structure of knowledge. Information visualization plays a key role in many areas such as decision-making, data mining, market studies, or knowledge management. A case of experiential learning was developed for Quantitative Techniques in Business and Administration and Economy Degrees at the University of Granada, Spain. The goal is to analyze the opinion of students (n = 227) on the development of the activity through information visualization techniques. The gathered information was subjected to a categorization process to unify and homogenize the responses. After a term-clumping process, a co-word analysis using the VosViewer software is used to analyze the relationships among terms and provide the network maps. Results display the main associations and clusters of terms used when assessing the experiential activity, using qualitative techniques. In conclusion, the strengths of data visualization enabling a better understanding of data for qualitative studies are established. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


Author(s):  
Feng Hu ◽  
Haibo Wei

Green finance issues have triggered the increasing research enthusiasm of researchers. With the rapid growing of publications related to green finance, it is difficult for readers to deeply understand the intellectual structure, research hotspots, and trends. In addition, the dynamic nature of a research front poses challenges for the scientists, research policymakers, and many others to keep up with the rapid advances of the state of the art in science. Therefore, the authors conducted a bibliometric analysis from the Web of Science over the period of 1998–2017. Co-word analysis and co-citation analysis are employed to explore institution distribution, journal co-citation analysis, author co-citation analysis, document co-citation analysis, and keyword co-word analysis, particularly in high frequency items, intellectual turning points, burst points, and emerging trends. The results can be useful for institutions and researchers worldwide to understand the panorama of green finance research, find the potential research gaps, and focus on the future research trends.


2019 ◽  
Vol 121 (1) ◽  
pp. 349-369 ◽  
Author(s):  
Xiuwen Chen ◽  
Jianping Li ◽  
Xiaolei Sun ◽  
Dengsheng Wu

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