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Scientific literature tends to grow as a function of funding and interest ina given field. Mining such literature can reveal trends that may not beimmediately apparent. The CORD-19 corpus represents a growing corpus ofscientific literature associated with COVID-19. We examined the intersection ofa set of candidate therapeutics identified in a drug-repurposing study withtemporal instances of the CORD-19 corpus to determine if it was possible tofind and measure changes associated with them over time. We propose that thetechniques we used could form the basis of a tool to pre-screen new candidatetherapeutics early in the research process.

Tracking Short-Term Temporal Linguistic Dynamics to Characterize Candidate Therapeutics for COVID-19 in the CORD-19 Corpus