Stem cell research: bibliometric analysis of main research areas through KeyWords Plus

Abstract

Purpose -Research with stem cells is a biomedical venture with great scientific impact, and whose development flows over into many other areas. This article presents a dual analysis of Spain´s scientific output in this field during the period 1997-2007.Design/methodology/approach -We used, on the one hand, bibliometric indicators of a basic nature, and on the other hand, techniques for the visualization and analysis of networks of scientific information based on a study of KeyWords Plus. Findings -The Output is mainly concentrated in Cataluña and Madrid, and hospitals are the most productive centres (followed by health institutes), where the main authors are affiliated. Main categories are Hematology, Oncology and Biophysics. The outstanding areas of study we identified revolve around the therapeutic use of transplant of hematopoietic progenitors, the processes of generation, proliferation and differentiation of lines of cells, and the study of neurosciences.Originality/value -This study provides an overview of Spanish research involving stem cells, detecting and representing the main areas of research. We consider the potential of KeyWords Plus in combination with the proposed methodology as particularly useful for the analysis and delimitation of a scientific domain.

Identification and Visualization of the Intellectual Structure in Graphene Research

“…In the light of previous experience involving keyword frequency and links (Zulueta et al, 2011;Cantos-Mateos et al, 2012Muñoz-Écija et al, 2017), we tagged each cluster, obtaining what would be the seven lines of research that support the knowledge structure of graphene research worldwide: Fundamental Research, Functionalization and Biomedical App lications, Technology and Devices, Materials Science, Energy Storage, Optics, and Chemical Properties and Sensors. According to the clustering algorithm used, the order of the clusters or research lines is determined by their number of keywords.…”

“…It is furthermore able to bring to light new developments of a research line over time (Peters and van Raan, 1993a,b) and help policy makers understand the complex interrelations of science and their implications for effective research planning (He, 1999). Although co-word analysis has gradually been improved upon, while not all of its limitations have been overcome (Wang et al, 2012), this type of analysis can reveal the intellectual underpinnings of a wide variety of domains: chemistry (Callon et al, 1991), data retrieval (Ding et al, 2001), the fuzzy logic field (López-Herrera et al, 2010), women and health (Zulueta et al, 2011), keyword analysis (Cantos-Mateos et al, 2012), human intelligence networks (Wang et al, 2012), and stem cells (Cantos-Mateos et al, 2014). A recent study applied it to study the intellectual structure of nanotechnology and its evolution (Muñoz-Écija et al, 2017).…”

Comparative evaluation of bibliometric content networks by tomographic content analysis: An application to Parkinson's disease

“…The Web of Science database (WoS) is the most widely used data set (Gu et al, ; Schäfer, Hiemke, & Baumann, ), whereas the SCOPUS database (Cheng & Zhang, ) or PubMed database (Ugolini et al, ) takes up a small fraction of the source of data sets. Knowledge entities, such as keywords in the title or abstract (Ho et al, ), or provided by authors (Li et al, ) or database provider (Cantos‐Mateos, Vargas‐Quesada, Chinchilla‐Rodríguez, & Zulueta, ), are used to observe research trends. In biomedical bibliometrics, MEDLINE searches are conducted to use the intended subject headings (Sorensen, Seary, & Riopelle, ; Ugolini, Puntoni, Perera, Schulte, & Bonassi, ).…”

Development of a methodology for scientometric analysis. application to study worldwide research on hardware architecture and cybernetics

“…In addition, it has been observed that most of these researches have been carried out in advanced countries like USA, European countries or G-8 Countries; for example USA (de Solla Price, 1976;Subramanyam, 1983;Vinkler, 2009), UK (Hamers et al, 1989;King, 1987;Rip & Courtial, 1984), Belgium (Garfield, 2009), Hungary (van Eck & Waltman, 2010), Nederlands (Cantos-Mateos et al, 2012), Spain (Montoya et al, 2014), etc. However, there is great variability in the areas studied, including worldwide studies.…”

“…This study demonstrates the feasibility of co-word analysis as a viable approach for extracting patterns from, and identifying trends, in large corpora where the texts collected are from the same domain or sub-domain and are divided into roughly equivalent quantities for different time periods. Also, Cantos-Mateos et al (Cantos-Mateos et al, 2012) answered the research questions about co-word categories and its related supply complementary information like usage of keywords as an adequate unit of analysis for thematic delimitation at the document level. He has also visualized this concept using software VOSviewer, while taking a matrix of co-occurrence of the more than 6,199 unique Keywords Plus, which were standardized by the measure of strength of association.…”