Datasets:
Tasks:
Text Classification
Formats:
csv
Languages:
Portuguese
Size:
10K - 100K
Tags:
hate-speech-detection
License:
Commit
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Parent(s):
e1df824
Update README.md
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README.md
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@@ -73,5 +73,20 @@ An illustration from the multilabel ToLD-Br dataset is depicted below:
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## Data Fields
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## Acknowledge
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The TuPy project is the result of the development of Felipe Oliveira's thesis and the work of several collaborators. This project is financed by the Federal University of Rio de Janeiro ([UFRJ](https://ufrj.br/)) and the Alberto Luiz Coimbra Institute for Postgraduate Studies and Research in Engineering ([COPPE](https://coppe.ufrj.br/)).
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```
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## Data Fields
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- Text: A string representing a anonymized tweet posted by a user. .
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- aggressive: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits aggressive language.
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- hate: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet is hateful.
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- ageism: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits ageism.
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- aporophobia: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits aporophobia.
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- body shame: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits body shame.
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- capacitism: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits capacitism.
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- lgbtphobia: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits lgbtphobia.
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- political: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits political.
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- racism: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits racism.
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- religious intolerance: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits religious intolerance.
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- misogyny: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits misogyny.
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- xenophobia: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits xenophobia.
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- other: Binary values (0 or 1) representing the consensus among annotators on whether the respective tweet exhibits other.
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## Acknowledge
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The TuPy project is the result of the development of Felipe Oliveira's thesis and the work of several collaborators. This project is financed by the Federal University of Rio de Janeiro ([UFRJ](https://ufrj.br/)) and the Alberto Luiz Coimbra Institute for Postgraduate Studies and Research in Engineering ([COPPE](https://coppe.ufrj.br/)).
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