All models and corresponding network visualizations are generated from documents in the CORD-19 dataset as of July 14, 2020. All annotations in red were added by the research team.
Note: These topic models are included here as additional reference and to append links to interactive versions on the Digital Scholarship Center’s machine learning platform for further exploration.
All models and corresponding network visualizations are generated from virus related documents in the CORD-19 dataset as of July 14, 2020. All annotations in red were added by the research team.
Note: Certain Non-Coronaviridae topic models are included in the text of this article and are included here only as additional reference and to append links to interactive versions on the Digital Scholarship Center’s machine learning platform for further exploration.
All models and corresponding network visualizations are generated from virus related documents in the CORD-19 dataset as of July, 2020. All annotations in red were added by the research team.
Note: Coronavirus topic models are included in the text of this article and are included here only as additional reference and to append links to interactive versions on the Digital Scholarship Center’s machine learning platform for further exploration.
These Centrality measurements were generated with NetworkX, a Python package for networks. The specific algorithms used for this paper are Betweenness Centrality (where Degree Centrality considers individual topics).
Complete Centrality Data for this research can be found at https://scholar.uc.edu/show/6t053h21x
Data Sets for HDSR publication "Convergence in Viral Epidemic Research: Using Natural Language Processing to Define Network Bridges in the Bench-Bedside-Population Paradigm" [remove]4