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COVIDScholar: An automated COVID-19 research aggregation and analysis platform
John Dagdelen1,2, Amalie Trewartha1, Haoyan Huo1,2
1Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America.
Plos One
|February 1, 2023
Summary
The COVID-19 pandemic spurred rapid research, necessitating new tools. COVIDScholar, an NLP-powered portal, organizes and finds over 260,000 COVID-19 research articles, patents, and trials.
Area of Science:
- Information Science
- Biomedical Informatics
- Computational Linguistics
Background:
- The COVID-19 pandemic generated an unprecedented volume of scientific literature, exceeding 250 papers daily.
- Traditional literature engagement methods were strained by the rapid dissemination of research through preprints and diverse channels.
- The urgency of the pandemic highlighted the need for advanced tools to manage and access scientific information.
Approach:
- Developed COVIDScholar, an automated knowledge portal utilizing natural language processing (NLP).
- Built a comprehensive corpus of over 260,000 COVID-19 research articles, patents, and clinical trials.
- Designed a search interface to facilitate efficient discovery of relevant scientific information.
Key Points:
- COVIDScholar served over 33,000 users, with peak usage of 8,600 weekly active users in summer 2020.
- The portal averaged 2,000 monthly active users, demonstrating significant adoption.
- Analysis of research trends during the first 10 months of the pandemic reveals rapid shifts in scientific focus.
Conclusions:
- COVIDScholar effectively addresses the challenge of navigating the vast COVID-19 research landscape.
- The NLP-driven portal enhances scientific literature organization and accessibility.
- The tool provides valuable insights into the evolving trends of pandemic-related research.
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