Tyrone Grandison
2020
Jennifer for COVID-19: An NLP-Powered Chatbot Built for the People and by the People to Combat Misinformation
Yunyao Li
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Tyrone Grandison
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Patricia Silveyra
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Ali Douraghy
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Xinyu Guan
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Thomas Kieselbach
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Chengkai Li
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Haiqi Zhang
Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020
Just as SARS-CoV-2, a new form of coronavirus continues to infect a growing number of people around the world, harmful misinformation about the outbreak also continues to spread. With the goal of combating misinformation, we designed and built Jennifer–a chatbot maintained by a global group of volunteers. With Jennifer, we hope to learn whether public information from reputable sources could be more effectively organized and shared in the wake of a crisis as well as to understand issues that the public were most immediately curious about. In this paper, we introduce Jennifer and describe the design of this proof-of-principle system. We also present lessons learned and discuss open challenges. Finally, to facilitate future research, we release COVID-19 Question Bank, a dataset of 3,924 COVID-19-related questions in 944 groups, gathered from our users and volunteers.
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Co-authors
- Yunyao Li 1
- Patricia Silveyra 1
- Ali Douraghy 1
- Xinyu Guan 1
- Thomas Kieselbach 1
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