COVIDScholar: An automated COVID-19 research aggregation and analysis platform

TL;DR

COVIDScholar is an NLP-powered platform that aggregates and analyzes COVID-19 research literature, patents, and clinical trials to help researchers navigate the overwhelming volume of emerging scientific information during the pandemic.

Contribution

It introduces a specialized knowledge portal utilizing NLP to synthesize COVID-19 research, addressing the challenge of information overload during the pandemic.

Findings

Over 81,000 COVID-19 papers indexed as of October 2020

The platform serves over 2000 users weekly

Analysis of research trends over 2020 provided insights into scientific focus areas

Abstract

The ongoing COVID-19 pandemic has had far-reaching effects throughout society, and science is no exception. The scale, speed, and breadth of the scientific community's COVID-19 response has lead to the emergence of new research literature on a remarkable scale -- as of October 2020, over 81,000 COVID-19 related scientific papers have been released, at a rate of over 250 per day. This has created a challenge to traditional methods of engagement with the research literature; the volume of new research is far beyond the ability of any human to read, and the urgency of response has lead to an increasingly prominent role for pre-print servers and a diffusion of relevant research across sources. These factors have created a need for new tools to change the way scientific literature is disseminated. COVIDScholar is a knowledge portal designed with the unique needs of the COVID-19 research community in mind, utilizing NLP to aid researchers in synthesizing the information spread across thousands of emergent research articles, patents, and clinical trials into actionable insights and new knowledge. The search interface for this corpus, https://covidscholar.org, now serves over 2000 unique users weekly. We present also an analysis of trends in COVID-19 research over the course of 2020.