CoV Index provides a map of Coronavirus Science, including Research, Research Communities, and Researchers.

CoV Index applies network analysis, bibliometrics, computer-human interaction, and computational linguistics methods to identify communities of Coronavirus research.

The primary goal of CoV Index is to support the comprehension of the massive - and growing - scientific archive of Coronavirus research. CoV Index seeks to organize Coronavirus Science so experts from any discipline can engage with Coronavirus Science.

Interdisciplinary Coronavirus Research

With the outbreak of COVID-19, Coronavirus research is gaining relevance to many scientific disciplines due to the impact Coronaviruses have upon society, economy, politics, psychology, and beyond. CoV Index bridges the gaps between academic disciplines. In this project, we analyze networks of scientific articles and researchers to build an index of interconnected Coronavirus resources.

Collaboration Network

The network of Coronavirus collaborators was extracted from a set of approximately 4000 articles. Any time researchers co-authored an article together, a network edge is created between them. The preliminary results are visualized below.

Contact

The CoV Index project is directed by Dr. Ian Dennis Miller.