
# 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  

{"language": ["multilingual", "nl", "fr", "en"], "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."}]}
transformers pytorch jax bert text-classification Dutch French English Tweets Topic classification multilingual nl fr en arxiv:2104.09947 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #jax #bert #text-classification #Dutch #French #English #Tweets #Topic classification #multilingual #nl #fr #en #arxiv-2104.09947 #autotrain_compatible #endpoints_compatible #region-us 


# Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
Blog post »   · paper »

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).

!URL


Models used in this paper are on HuggingFace:  
- URL  
- URL  

# Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
Blog post »   · paper »

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).

!URL


Models used in this paper are on HuggingFace:  
- URL  
- URL
TAGS
#transformers #pytorch #jax #bert #text-classification #Dutch #French #English #Tweets #Topic classification #multilingual #nl #fr #en #arxiv-2104.09947 #autotrain_compatible #endpoints_compatible #region-us 
 # Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
Blog post »   · paper »

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).

!URL


Models used in this paper are on HuggingFace:  
- URL  
- URL
passage: TAGS
#transformers #pytorch #jax #bert #text-classification #Dutch #French #English #Tweets #Topic classification #multilingual #nl #fr #en #arxiv-2104.09947 #autotrain_compatible #endpoints_compatible #region-us 
# Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
Blog post »   · paper »

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).

!URL


Models used in this paper are on HuggingFace:  
- URL  
- URL