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COVID 19 literature NLP models - Viral outbreak model centrality files Open Access Deposited

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Date Uploaded: 10/29/2020
Date Modified: 11/05/2020

The data sets were derived from coronavirus related scientific literature using the CORD-19 dataset released by the Allen Institute of Artificial Intelligence as of July 14, 2020, using the Elasticsearch engine hosted by the Digital Scholarship Center (DSC). Through indexing the full-text and the metadata of the article corpus, the research team generated a full-corpus model and 7 different models corresponding to key viral outbreaks from the past several decades' coronaviruses (SARS-CoV, MERS-CoV, and SARS- CoV-2) and non-coronaviruses (HIV, Zika, H1N1, and Ebola). The targeted subsets of the articles used two or more occurrences of virus-specific keywords drawn from conventions established by the World Health Organization.

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Thumbnail Title Date Uploaded Visibility Actions
README_file_model_centrality.docx 2020-11-04 Open Access
100_rand_topics.csv 2020-10-29 Open Access
10k_rand_docs_centrality_topics.csv 2020-10-29 Open Access
covid-19_centrality_topics_q1.csv 2020-10-29 Open Access
covid-19_centrality_topics_q2.csv 2020-10-29 Open Access
covid-19_centrality_topics_total.csv 2020-10-29 Open Access
Ebola_centrality_topics.csv 2020-10-29 Open Access
Ebola_centrality_topics_excl_covid19.csv 2020-10-29 Open Access
full_corpus_centrality_topics.csv 2020-10-29 Open Access
H1N1_centrality_topics.csv 2020-10-29 Open Access

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