Corpus ID: 218889670

What Are People Asking About COVID-19? A Question Classification Dataset

@article{Wei2020WhatAP,
  title={What Are People Asking About COVID-19? A Question Classification Dataset},
  author={Jerry W. Wei and Chengyu Huang and Soroush Vosoughi and Jason Wei},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.12522}
}
We present COVID-Q, a set of 1,690 questions about COVID-19 from 13 sources, which we annotate into 15 question categories and 207 question clusters. The most common questions in our dataset asked about transmission, prevention, and societal effects of COVID, and we found that many questions that appeared in multiple sources were not answered by any FAQ websites of reputable organizations such as the CDC and FDA. We post our dataset publicly at https://github.com/JerryWei03/COVID-Q. For… Expand
Answering Questions on COVID-19 in Real-Time
A Dashboard for Mitigating the COVID-19 Misinfodemic
A Proposed Chatbot Framework for COVID-19
Few-Shot Text Classification with Triplet Networks, Data Augmentation, and Curriculum Learning
...
1
2
...

References

SHOWING 1-10 OF 16 REFERENCES
Diverse Few-Shot Text Classification with Multiple Metrics
NAIST COVID: Multilingual COVID-19 Twitter and Weibo Dataset
A First Instagram Dataset on COVID-19
Measuring Emotions in the COVID-19 Real World Worry Dataset
...
1
2
...