Abstract
The COVID-19 outbreak pandemic is a situation without a tested action plan. Rehabilitation team members have been called for duty with new responsibilities in addition to their conventional roles in the healthcare system. The infectious disease specialists are updating the knowledge base in limited time in clinical settings. The number of articles in PubMed grows at an increasing rate. The purpose of this study is to identify core COVID-19 articles by citation and co-citation network analysis in the PMC subset of PubMed. Citation and co-citation network analysis methods were used to identify core articles and knowledge base. COVID-19 terms query retrieved 15,387 articles in PubMed. These articles formed a citation network with 6,778 articles and 25,163 PMC-PubMed citations. The main article cluster in the co-citation network consists of 2,811 articles and 78,844 co-citations. The number of COVID-19 articles in PubMed is increasing at a very high rate. Citation and co-citation network analysis are advantageous techniques to identify knowledge base in a scientific discipline. These techniques may help rehabilitation specialists to identify core articles efficiently.
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