Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
License:
Update README.md
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README.md
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license: apache-2.0
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license: apache-2.0
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- 33.058 texts in total, 14.491 NOT hateful texts and 18.567 HATEFUL texts
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- All duplicate values were removed
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- Split using sklearn into 80% train and 20% temporary test (stratified label). Then split the test set using 0.50% test and validation (stratified label)
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- Split: 80/10/10
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- Train set label distribution: 0 ==> 11.593, 1 ==> 14.853
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- Validation set label distribution: 0 ==> 1.449, 1 ==> 1.857
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- Test set label distribution: 0 ==> 1.449, 1 ==> 1.857
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- Combination of 4 publicly available datasets:
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- 1."Ethos" dataset (Mollas et al., 2022)
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- 2. HateCheck: Functional Tests for Hate Speech Detection Models (Rottger et al., 2021)
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- 3. A Benchmark Dataset for Learning to Intervene in Online Hate Speech (Qian et al., 2019)
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- 4. Automated Hate Speech Detection and the Problem of Offensive Language (Davidson, et al., 2017)
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