Papers
arxiv:2104.09947
Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
Published on Apr 20, 2021
Abstract
Tweets about Belgian government curfew measures during COVID-19 are classified using multilingual BERT, examining changes in opinion over time.
AI-generated summary
We classify seven months' worth of Belgian COVID-related Tweets using multilingual BERT and relate them to their governments' COVID measures. We classify Tweets by their stated opinion on Belgian government curfew measures (too strict, ok, too loose). We examine the change in topics discussed and views expressed over time and in reference to dates of related events such as implementation of new measures or COVID-19 related announcements in the media.
Get this paper in your agent:
hf papers read 2104.09947 Don't have the latest CLI?
curl -LsSf https://hf.co/cli/install.sh | bash Models citing this paper 2
Datasets citing this paper 0
No dataset linking this paper
Cite arxiv.org/abs/2104.09947 in a dataset README.md to link it from this page.
Spaces citing this paper 0
No Space linking this paper
Cite arxiv.org/abs/2104.09947 in a Space README.md to link it from this page.
Collections including this paper 0
No Collection including this paper
Add this paper to a collection to link it from this page.