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CORD-19

Natural language processing code for coronavirus corpus CORD-19

This repository is for computational linguistics, natural language processing, and text mining tools for working with the CORD-19 corpus of papers related to the COVID-19 Open Research Dataset. See here for information on the dataset itself:

https://pages.semanticscholar.org/coronavirus-research

CORD-19-JSON-Parser.Rmd/.html: Parses the CORD-19 JSON files and pulls out the important text.

CORD-19 Word Cloud.Rmd/.html: A COVID-19-specific word cloud, analysis of word associations, and analysis of lexical frequencies. NOTE: Any other versions of WordCloud code in here are deprecated.

CORD-19 Text clustering experiments.Rmd/.html: Simple text clustering experiments using K-means and hierarchical clustering. Various parameters are varied.

lexicalFrequency.pl: Raw frequencies of words, without preprocessing.

overrepresentedWords.pl: Run this on the output of lexicalFrequency.pl to get over-represented words in the corpus.

test.overrepresented.01/.02.txt: Test data for overrepresentedWords.pl

cord-19's People

Contributors

kevinbretonnelcohen avatar

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James Cloos avatar  avatar

cord-19's Issues

JSON Parser needs TITLE+ABSTRACT option

Currently pulls text from titles, or abstracts, or the article body, or the full paper---but, not title + abstract, which seems like a reasonable unit of analysis.

Feature request: Over-represented words script: get over-represented words in the reference corpus

Currently I get the words that are over-represented in the corpus of interest as compared to the reference corpus, but not the ones that are over-represented in the reference corpus as compared to the corpus of interest. That's fine from the point of view of the research questions about the corpus of interest, but knowing which words are "over-represented" in the reference corpus as compared to the corpus of interest is a good sanity check on the functioning of the script, so let's add that in, too. It's a simple return to the previous approach of calculating the ratios for the union of the words in the vocabularies, rather than the ratios for only those words that are in the corpus of interest.

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