Datasets:
metadata
language:
- en
- ru
- uk
- de
- es
- am
- zh
- ar
- hi
license: openrail++
size_categories:
- 10K<n<100K
task_categories:
- text-classification
dataset_info:
features:
- name: text
dtype: string
- name: toxic
dtype: int64
splits:
- name: en
num_bytes: 411178
num_examples: 5000
- name: ru
num_bytes: 710001
num_examples: 5000
- name: uk
num_bytes: 630595
num_examples: 5000
- name: de
num_bytes: 941017
num_examples: 5000
- name: es
num_bytes: 978750
num_examples: 5000
- name: am
num_bytes: 1102628
num_examples: 5000
- name: zh
num_bytes: 359235
num_examples: 5000
- name: ar
num_bytes: 889661
num_examples: 5000
- name: hi
num_bytes: 1842662
num_examples: 5000
download_size: 4470012
dataset_size: 7865727
configs:
- config_name: default
data_files:
- split: en
path: data/en-*
- split: ru
path: data/ru-*
- split: uk
path: data/uk-*
- split: de
path: data/de-*
- split: es
path: data/es-*
- split: am
path: data/am-*
- split: zh
path: data/zh-*
- split: ar
path: data/ar-*
- split: hi
path: data/hi-*
For the shared task CLEF TextDetox 2024, we provide a compilation of binary toxicity classification datasets for each language. Namely, for each language, we provide 5k subparts of the datasets -- 2.5k toxic and 2.5k non-toxic samples.
The list of original sources:
- English: Jigsaw, Unitary AI Toxicity Dataset
- Russian: Russian Language Toxic Comments, Toxic Russian Comments
- Ukrainian: our labeling based on Ukrainian Twitter texts
- Spanish: CLANDESTINO, the Spanish toxic language dataset
- German: DeTox-Dataset, GemEval 2018, 2021
- Amhairc: Amharic Hate Speech
- Arabic: OSACT4
- Hindi: Hostility Detection Dataset in Hindi, Overview of the HASOC track at FIRE 2019: Hate Speech and Offensive Content Identification in Indo-European Languages
All credits go to the authors of the original toxic words lists.