Datasets:
Tasks:
Text Classification
Formats:
csv
Languages:
Portuguese
Size:
10K - 100K
ArXiv:
Tags:
hate-speech-detection
License:
victoriadreis
commited on
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Update README.md
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README.md
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To safeguard user identity and uphold the integrity of this dataset, all user mentions have been anonymized as "@user," and any references to external websites have been omitted
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## Annotation and voting process
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If a document received two or more identical classifications, the assigned value was set to 1; otherwise, it was marked as 0.
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The annotated raw data can be accessed in the [project repository](https://github.com/Silly-Machine/TuPy-Dataset).
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The following table offers a brief summary of the annotators' profiles and qualifications:
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| Label | Count |
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|----------------------|--------|
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| Non-aggressive |
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| Aggressive - Not hate|
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| Aggressive - Hate |
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| Total |
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Table 3 provides a detailed analysis of the dataset, delineating the data volume in relation to the occurrence of distinct categories of hate speech.
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| Label | Count |
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|--------------------------|-------|
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| Ageism |
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| Aporophobia |
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| Body shame |
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| Capacitism |
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| LGBTphobia |
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| Political |
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| Racism |
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| Religious intolerance |
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| Misogyny |
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| Xenophobia |
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| Other |
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| Total |
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# BibTeX citation
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To safeguard user identity and uphold the integrity of this dataset, all user mentions have been anonymized as "@user," and any references to external websites have been omitted
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## Annotation and voting process
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Regarding the unpublished part of the TuPyE dataset, we utilized a simple voting process to generate the binary matrices. Each document underwent three separate evaluations.
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If a document received two or more identical classifications, the assigned value was set to 1; otherwise, it was marked as 0.
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The annotated raw data can be accessed in the [project repository](https://github.com/Silly-Machine/TuPy-Dataset).
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The following table offers a brief summary of the annotators' profiles and qualifications:
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| Label | Count |
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|----------------------|--------|
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| Non-aggressive | 31121 |
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| Aggressive - Not hate| 3180 |
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| Aggressive - Hate | 9367 |
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| Total | 43668 |
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Table 3 provides a detailed analysis of the dataset, delineating the data volume in relation to the occurrence of distinct categories of hate speech.
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| Label | Count |
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|--------------------------|-------|
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| Ageism | 57 |
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| Aporophobia | 66 |
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| Body shame | 285 |
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| Capacitism | 99 |
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| LGBTphobia | 805 |
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| Political | 1149 |
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| Racism | 290 |
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| Religious intolerance | 108 |
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| Misogyny | 1675 |
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| Xenophobia | 357 |
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| Other | 4476 |
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| Total | 9367 |
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# BibTeX citation
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