Bibliometric and Text Mining Analysis on COVID-19 Research Projects in Iran

In response to the COVID-19 epidemic, researchers around the world conducted various studies on different dimensions of the disease. Accordingly, this study aimed at investigating the structure and topics of COVID-19 research projects approved in Iran.

This applied research, adopting an analytical approach, was conducted using bibliometric and text mining methods. The statistical population was the COVID-19 research projects approved in Iran in 2020. These research projects were extracted from the database of Iran national committee for ethics in biomedical research (ethics.research.ac.ir). To identify the topics of the research projects on COVID-19 for text mining the English Language titles of the projects were used, topic modeling algorithms was done by the Python programming language.

We selected a total of 6641 COVID-19 research projects approved and conducted in 93 different Iranian universities and research centers. .of the main bulk of the research in this area had been conducted by Tehran University of Medical Sciences, Shahid Beheshti University of Medical Sciences, and Shiraz University of Medical Sciences including 687,662, and 351 cases respectively. COVID-19 Research projects fell into 12 topical categories including Treatment, Care needs of medical staff, Factors affecting disease severity, Mental health and preventive, Diagnostic and laboratory measures, Immunology studies, Vitamins and minerals, Cardiovascular disease, Vaccine studies, Job and life stress, Experiences of nurses, patients and their families and Prevalence and symptoms.

The results of this study clearly show the structural and topic status of research COVID-19 projects approved in Iran during the COVID-19 epidemic.