pytorch jax bert text-classification multilingual arxiv:2104.09947 transformers Dutch French English Tweets Topic classification
.gitattributes README.md config.json flax_model.msgpack pytorch_model.bin tokenizer_config.json vocab.txt
---
language: "multilingual"
tags:
- Dutch
- French
- English
- Tweets
- Topic classification
widget:
 - text: "I really can't wait for this lockdown to be over and go back to waking up early."
---

# Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
[Blog post »](https://people.cs.kuleuven.be/~pieter.delobelle/attitudes-towards-covid-19-measures/?utm_source=huggingface&utm_medium=social&utm_campaign=corona_tweets)   · [paper »](http://arxiv.org/abs/2104.09947)

We categorized several months worth of these Tweets by topic (government COVID measure) and opinion expressed. Below is a timeline of the relative number of Tweets on the curfew topic (middle) and the fraction of those Tweets that find the curfew too strict, too loose, or a suitable measure (bottom), with the number of daily cases in Belgium to give context on the pandemic situation (top).

![chart.png](https://github.com/iPieter/bert-corona-tweets/raw/master/chart.png)


Models used in this paper are on HuggingFace:  
- https://huggingface.co/DTAI-KULeuven/mbert-corona-tweets-belgium-curfew-support  
- https://huggingface.co/DTAI-KULeuven/mbert-corona-tweets-belgium-topics  
