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Introduction to the 1st Workshop on Natural Language Processing for COVID-19 at ACL 2020

机译:ACL 2020的Covid-19自然语言处理的第一个研讨会简介

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The unprecedented global pandemic related to the spread of the coronavirus SARS-COV-2 and the associated outbreak of the infection dubbed COVID-19 has had dramatic impacts worldwide during 2020. Scientists around the globe have responded to the pandemic, hoping to make some contribution to understanding, tracking, modeling, and/or responding. The ACL community can play a unique role in supporting research to combat COVID-19. Valuable insights and critical information may be contained in vast quantities of unstructured text and speech data. Thousands of previously published research articles (and those being published on a daily basis) on coronavirus may shape our understanding of the virus or support best practice clinical management of the disease. Analysis of millions of social media posts may help us understand how the public at large is responding to the outbreak. Identifying spreading misinformation can be critical to public health messaging. Automatic identification and organization of helpful information collected from the web might aid public response.
机译:与冠状病毒SARS-COV-2的传播有关的前所未有的全球大流行,并将Covid-19称为COVID-19的相关爆发在2020年期间在全球范围内产生了巨大的影响。全球科学家们对大流行作出了回应,希望有一些贡献理解,跟踪,建模和/或响应。 ACL社区可以在支持COVID-19的支持方面发挥独特作用。有价值的见解和关键信息可以包含在大量非结构化文本和语音数据中。在冠状病毒上,成千上万的出版的研究文章(以及每天发表的那些)冠状病毒可能会塑造我们对病毒的理解或对疾病的最佳实践临床管理。分析数百万社交媒体职位可能有助于我们了解公众的大量是如何应对爆发。识别扩散错误信息对公共卫生消息传递至关重要。自动识别和组织从网络中收集的有用信息可能有助于公众回应。

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