Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
License:
| license: apache-2.0 | |
| task_categories: | |
| - text-classification | |
| language: | |
| - en | |
| - 44.246 texts in total, 21.493 NOT hateful texts and 22.753 HATE 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 ==> 17.194, 1 ==> 18.202, 35.396 in total | |
| - Validation set label distribution: 0 ==> 2.150, 1 ==> 2.275, 4.425 in total | |
| - Test set label distribution: 0 ==> 2.149, 1 ==> 2.276, 4.425 in total | |
| - Combination of 6 publicly available datasets: | |
| - 1. "Ethos" dataset (Mollas et al., 2022) | |
| - 2. Anatomy of Online Hate: Developing a Taxonomy and Machine Learning Models for Identifying and Classifying Hate in Online News Media (Salminem et al. (2018) | |
| - 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) | |
| - 5. HatEval (Basile et al, 2019), SemEval-2019 Task 5 | |
| - 6. "Hate Towards the Political Opponent"(Grimminger et al., 2021) |