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COVIDScholar:一个自动化的 COVID-19 研究聚合和分析平台。

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

机构信息

Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America.

Department of Materials Science & Engineering, University of California, Berkeley, Berkeley, CA, United States of America.

出版信息

PLoS One. 2023 Feb 1;18(2):e0281147. doi: 10.1371/journal.pone.0281147. eCollection 2023.

Abstract

The ongoing COVID-19 pandemic produced far-reaching effects throughout society, and science is no exception. The scale, speed, and breadth of the scientific community's COVID-19 response lead to the emergence of new research at the remarkable rate of more than 250 papers published per day. This posed a challenge for the scientific community as traditional methods of engagement with the literature were strained by the volume of new research being produced. Meanwhile, the urgency of response lead to an increasingly prominent role for preprint servers and a diffusion of relevant research through many channels simultaneously. These factors created a need for new tools to change the way scientific literature is organized and found by researchers. With this challenge in mind, we present an overview of COVIDScholar https://covidscholar.org, an automated knowledge portal which utilizes natural language processing (NLP) that was built to meet these urgent needs. The search interface for this corpus of more than 260,000 research articles, patents, and clinical trials served more than 33,000 users at an average of 2,000 monthly active users and a peak of more than 8,600 weekly active users in the summer of 2020. Additionally, we include an analysis of trends in COVID-19 research over the course of the pandemic with a particular focus on the first 10 months, which represents a unique period of rapid worldwide shift in scientific attention.

摘要

持续的 COVID-19 大流行对整个社会产生了深远的影响,科学界也不例外。科学界对 COVID-19 的反应规模、速度和广度导致了新研究的出现,其速度惊人,每天发表的论文超过 250 篇。这对科学界来说是一个挑战,因为传统的文献参与方法因新研究的数量而受到限制。与此同时,应对的紧迫性导致预印本服务器的作用越来越突出,同时通过许多渠道同时传播相关研究。这些因素需要新的工具来改变研究人员组织和发现科学文献的方式。考虑到这一挑战,我们介绍了 COVIDScholar https://covidscholar.org,这是一个自动化的知识门户,利用自然语言处理 (NLP) 技术来满足这些紧迫的需求。该语料库包含超过 26 万篇研究文章、专利和临床试验,其搜索界面为 33000 多名用户提供服务,平均每月活跃用户为 2000 名,2020 年夏季的每周活跃用户峰值超过 8600 名。此外,我们还分析了 COVID-19 研究在大流行期间的趋势,特别关注前 10 个月,这代表了全球科学界注意力迅速转变的独特时期。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bb/9891495/44bd67fcb471/pone.0281147.g001.jpg

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