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Jennifer for COVID-19: An NLP-Powered Chatbot Built for the Peopleand by the People to Combat Misinformation

Li, Yunyao (author)
IBM Research - Almaden
Grandison, Tyrone (author)
The Data-Driven Institute
Silveyra, Patricia (author)
University of North Carolina - Chapel Hill
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Douraghy, Ali (author)
The National Academies of Sciences, Engineering and Medicine
Guan, Xinyu (author)
Yale University
Kieselbach, Thomas (author)
Umeå universitet,Umeå universitetsbibliotek (UB)
Li, Chengka (author)
University of Texas - Arlington
Zhang, Haiqi (author)
University of Texas - Arlington
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 (creator_code:org_t)
2020
2020
English.
In: Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020.
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Just as SARS-CoV-2 continues to infect a growing number of people around the world, harmful misinformation about the outbreak also continues to spread. We designed and built Jennifer chatbot to provide easily accessible information from reliable resources to answer questions related to the current COVID-19 pandemic. It covers a wide variety of topics, from case statistics to best practices for disease prevention and management.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Language Technology (hsv//eng)

Keyword

Natural Language Processing
Covid-19
Information
Misinformation
language studies
språkvetenskap
data- och systemvetenskap
computer and systems sciences
Medicine
medicin

Publication and Content Type

ref (subject category)
kon (subject category)

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