Jennifer for COVID-19: An NLP-Powered Chatbot Built for the People and by the People to Combat Misinformation
Keywords: chatbot, fact checking, misinformation, crowdsourcing, case study, application, dataset, multilingual
TL;DR: This paper introduces Jennifer, a chatbot created to provide easily accessible information from reliable resources to answer questions related to the current COVID-19 pandemic.
Abstract: 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 COQB-19 (COVID-19 Question Bank, available at https://www.newvoicesnasem.org/data-downloads), a dataset of 3,924 COVID-19-related questions in 944 groups, gathered from our users and volunteers. Jennifer is available at http://bit.ly/jenniferai and on Facebook at http://fb.me/JenniferCOVIDAI.