README.md

---
license: apache-2.0
task_categories:
- text-classification
language:
- en
---

- 32.579 texts in total, 14.012 NOT hateful texts and 18.567 HATEFUL texts
- All duplicate values were removed
- 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)
- Split: 80/10/10
- Train set label distribution: 0 ==> 11.210, 1 ==> 14.853,  26.063 in total
- Validation set label distribution: 0 ==> 1.401, 1 ==> 1.857,  3.258 in total
- Test set label distribution: 0 ==> 1.401, 1 ==> 1.857,  3.258 in total
- Combination of 4 publicly available datasets:
- 1. "Ethos" dataset (Mollas et al., 2022)
- 2. HateCheck: Functional Tests for Hate Speech Detection Models (Rottger et al., 2021)
- 3. A Benchmark Dataset for Learning to Intervene in Online Hate Speech (Qian et al., 2019)
- 4. Automated Hate Speech Detection and the Problem of Offensive Language (Davidson, et al., 2017)