Abstract: The analysis of the network structure of COVID-19’s review literature can provide effective theoretical support for COVID-19’s response to the epidemic situation. The co-citation network analysis of COVID-19’s review literature in Web of Science database is carried out by using visualization software CiteSpace. Through statistics, it is found that the degree distribution of literature co-citation network is power-law distribution, network connectivity is strong and there is a small-world phenomenon. The clique percorlation method is used to mine the overlapping communities, and seven core literatures which span three communities at the same time are detected. Combined with the cited frequency, the function of the network overlapping nodes is verified. With the help of ID symbols and intermediate centrality index of network overlapping nodes, it is found that the corresponding research topics are closely related. Through the important network nodes with different characteristics, we can effectively mine the relevant research topics.

Key words: COVID-19, literature co-citation network, overlapping community detection, CiteSpace