Background: When the COVID-19 outbreak spreads to the world, many articles related to it have been published in academics. Since the largest quantity of confirmed cases was reported in China till April 14, 2020, whether the number of Chinese articles of research associated with the COVID-19 topped globally is required to be examined. Thus, an objective measure determining the dominant role in a group should be defined. This study aims to propose an index (strength coefficient, SC) to evaluate the most influential research affiliations in publications of COVID-19. Methods: We simulated data to verify the separation index that can be viable in use for determining the dominant one that has the absolute advantage in a group. We selected 4,369 articles as of April 14, 2020, with abstracts from the Pubmed Central (PMC) based on the keywords COVID-19 or 2019-nCOV. An author-weighted scheme (AWS) was applied to quantify coauthor credits in the article byline. Social network analysis incorporated with SC(from 0 to 1.0 and cutoff=0/70) was applied to display the influential (1) article types, (2)countries, (3)medical subject headings(MeSH terms), and (4) research affiliations. Visual dashboards were created for displaying the results on Google Maps. Results: We observed that the top one(SC) in each topic consists of (1) journal article(0.81), (2) China(0.61),(3) Acad Radol, (4) betacoronavirus (0.66), and (5) Hazhong University of Science and Technology(0.77) in article types, countries, journals, MeSH terms, and research affiliations, respectively. Conclusion: We applied the SC to identify the strength of the top one over the next two. The SC was useful and viable in verifying the dominant role in a group. The implementation and application are worthy of further studies in the future.