Dataset

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.

创建者

• Koshoffer, Amy
• Wu, Danny
• Latessa, Jenny
• Lee, James
• Luken, Sally
• McCabe, Erin
• Edgerton, Ezra
• Washington, Dorcas
• Kannayyagar, Suraj
• Powers, Margaret

证书

• CC0 1.0 Universal

学科

• Natural Language Processing
• Viruses
• COVID 19

提交

Amy Koshoffer

学

• Libraries

部门

• Research & Data Services, Data Scien

创建日期

• 2020-07

出版者

• University of Cincinnati

语言

• English

关系

在收集：

• Data Sets for HDSR publication "Convergence in Viral Epidemic Research: Using Natural Language Processing to Define Network Bridges in the Bench-Bedside-Population Paradigm"

单件

缩略图	标题	上传日期	公开度	行动
	README_file_model_centrality.docx	2020-11-04	开放存取	Press to 选择一个动作 下载
	100_rand_topics.csv	2020-10-29	开放存取	Press to 选择一个动作 下载
	10k_rand_docs_centrality_topics.csv	2020-10-29	开放存取	Press to 选择一个动作 下载
	covid-19_centrality_topics_q1.csv	2020-10-29	开放存取	Press to 选择一个动作 下载
	covid-19_centrality_topics_q2.csv	2020-10-29	开放存取	Press to 选择一个动作 下载
	covid-19_centrality_topics_total.csv	2020-10-29	开放存取	Press to 选择一个动作 下载
	Ebola_centrality_topics.csv	2020-10-29	开放存取	Press to 选择一个动作 下载
	Ebola_centrality_topics_excl_covid19.csv	2020-10-29	开放存取	Press to 选择一个动作 下载
	full_corpus_centrality_topics.csv	2020-10-29	开放存取	Press to 选择一个动作 下载
	H1N1_centrality_topics.csv	2020-10-29	开放存取	Press to 选择一个动作 下载