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  - English
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  - Tweets
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  - Sentiment analysis
 
 
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  ---
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  # Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
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  [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)
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  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).
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  ![chart.png](https://github.com/iPieter/bert-corona-tweets/raw/master/chart.png)
 
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  - English
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  - Tweets
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  - Sentiment analysis
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+ widget:
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+ - text: "I really wish I could leave my house after midnight, this makes no sense!"
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  ---
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  # Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
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  [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)
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+ This model can be used to determine if a tweet expresses support or not for a curfew. The model was trained on manually labeled tweets from Belgium in Dutch, French and English.
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  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).
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  ![chart.png](https://github.com/iPieter/bert-corona-tweets/raw/master/chart.png)