Abstract

Using visualization techniques based on social networks, this study aims to analyze stem cell research in Spain, as reflected in the Science Citation Index (SCI) database between 1997 and 2010 , divided into three sub-periods. The selected unit of analysis was the KeyWords Plus descriptors (KW+), the unit of measurement was their co-occurrence , and the Pajek and VOSviewer tools were used to generate and display the social networks. The results show two complementary images of research: the static structure, distinguishing between clinical and basic research, and the evolutionary dynamic, analysing both the most established and the emerging lines. The main contribution of this work is to present a methodology for the visualization and detection of the main r esearch lines over time, demonstrating its applicability and its predictability in scientific and geographic domains.

Abstract

Covid-19 represents the greatest challenge facing mankind today. In December 2019, several cases of pneumonia of unknown etiology were reported from China. This coronavirus infection subsequently identified as Covid-19 aroused worldwide concern. As a result, the scientific community has focused attention on Covid-19, as revealed by recent research reported in literature based on a holistic approach. In this regard, this study conducts a bibliometric analysis of coronavirus research in the literature with an emphasis on Covid-19 disease, using as a reference the publications in the Web of Science Core Collection from 1970 to 2020. This research analyzes 12,571 publications from 1970 to (April 18) 2020 by applying advanced bibliometric techniques in SciMAT bibliometric analysis software. The current research therefore provides a complete conceptual analysis of the main coronavirus types and strains in the literature by quantifying the main bibliometric performance indicators, identifying the main authors, organizations, countries, sources, and research areas, and evaluating the development of this field. Furthermore, a science map is constructed to understand the corresponding intellectual structure and main research lines (themes). SciMAT thereby offers a complete approach to the field and evaluates the main performance indicators related to coronavirus, with a focus on Covid-19. Finally, this research serves as a framework to strengthen existing research lines and develop new ones, establishing synergistic relationships that were not visible without the maps generated herein.