Análisis bibliométrico de la producción científica sobre el efecto COVID- 19 en las Ciencias de la Información

The COVID-19 pandemic has caused one of the largest global health crises in recent years. The search for solutions to the global public health problem has impacted many aspects of our society; one of them is scientific information and communication, which initially faced a lack of supporting study data. The scientific community has reacted quickly to the medical challenges generated by the pandemic. From various disciplines, researchers began to publish their findings in order to share information to deal with the health crisis, which led to an unprecedented growth in knowledge. The peak of publications following the 2019 coronavirus outbreak was unprecedented: in less than five months, more than 12,000 research articles were indexed, and in less than seven, more than 30,000 articles. Scientists around the world are conducting research at breakneck speeds to address the problem.

In turn, the need to reduce the publication time for articles on COVID-19 has accelerated the peer review process, so much so that the publication rules for research papers are being changed(4) (preprint servers, where scientists publish manuscripts before peer review, have been overwhelmed with studies that are subsequently disseminated on social media and platforms such as Twitter). The enormous demand to produce evidence related to COVID-19, which can provide a knowledge base for making effective clinical decisions or to know the main research fronts in this field, has become essential. In addition to the orientation of research towards epidemiological topics related to virology, research on COVID-19 seems to have become a focal point of interest in many and diverse academic disciplines, such as computer science, or as seen in the case of research in library science and information studies.(7) From a bibliometric approach, which is the one in which this study is framed, there are many investigations aimed at the exponential growth of scientific production on this disease.

In general, bibliometric analysis is directed at studies that account for the growing pace of scientific production, the research fronts and trends, the institutions and countries involved or the most relevant topics. Metric studies are basically based on the quantitative analysis of statistical data extracted from published literature, using two types of basic measures: 1) unidimensional indicators, based on univariate statistical techniques, dedicated to analyzing or measuring a single characteristic of the selected documents, without taking into account any link that may exist between them; 2) multidimensional indicators, based on multivariate statistical techniques, dedicated to simultaneously analyzing or measuring different units of analysis or variables observed in the selected documents. Metric analyses are continuously experiencing the development of new tools for analyzing and visualizing information, which contribute to the interest in carrying out this type of research.The purpose of this work was to apply bibliometric techniques to analyze and visualize the impact of scientific production on the COVID-19 disease in the field of
Library and Information Science (LIS) knowledge.