Datasets:

gravitee-io
/

textdetox-multilingual-toxicity-dataset

language:
  - en
  - ru
  - uk
  - de
  - es
  - am
  - zh
  - ar
  - hi
  - it
  - fr
  - he
  - ja
  - tt
license: openrail++
size_categories:
  - 10K<n<100K
task_categories:
  - text-classification
datasets:
  - textdetox/multilingual_toxicity_dataset
dataset_info:
  features:
    - name: text
      dtype: string
    - name: toxic
      dtype: int64
    - name: labels
      dtype: string
    - name: language
      dtype: string
  splits:
    - name: train
      num_bytes: 10733659
      num_examples: 60667
    - name: test
      num_bytes: 1893353
      num_examples: 10707
configs:
  - config_name: default
    data_files:
      - split: train
        path: train/data-*
      - split: test
        path: test/data-*

TextDetox Multilingual Toxicity Classification Dataset

This repository provides a multilingual dataset for binary toxicity classification across 14 languages, derived from the TextDetox: Multilingual Toxicity Dataset. The dataset has been split into 85/15 train/test sets for each language, ensuring a representative and balanced sampling.

Dataset Overview

Task: Text classification (toxic vs. non-toxic)
Split ratio: 85% training / 15% testing
License: OpenRAIL++

Features

Feature	Type	Description
text	string	The user-generated comment
toxic	int64	1 if toxic, 0 if not-toxic
language	string	the language of the text
labels	string	toxic column value as string

Source

The dataset is based entirely on the TextDetox: Multilingual Toxicity Dataset. All credits for data collection, annotation, and multilingual coverage go to the original authors. This repository provides only a derived version of the data for training and evaluation purposes.

Citation

@inproceedings{dementieva2024overview,
  title={Overview of the Multilingual Text Detoxification Task at PAN 2024},
  author={Dementieva, Daryna and Moskovskiy, Daniil and Babakov, Nikolay and Ayele, Abinew Ali and Rizwan, Naquee and Schneider, Frolian and Wang, Xintog and Yimam, Seid Muhie and Ustalov, Dmitry and Stakovskii, Elisei and Smirnova, Alisa and Elnagar, Ashraf and Mukherjee, Animesh and Panchenko, Alexander},
  booktitle={Working Notes of CLEF 2024 - Conference and Labs of the Evaluation Forum},
  editor={Guglielmo Faggioli and Nicola Ferro and Petra Galu{{s}}{{c}}{'a}kov{'a} and Alba Garc{'i}a Seco de Herrera},
  year={2024},
  organization={CEUR-WS.org}
}

@inproceedings{dementieva-etal-2024-toxicity,
  title = "Toxicity Classification in {U}krainian",
  author = "Dementieva, Daryna and Khylenko, Valeriia and Babakov, Nikolay and Groh, Georg",
  editor = {Chung, Yi-Ling and Talat, Zeerak and Nozza, Debora and Plaza-del-Arco, Flor Miriam and R{"o}ttger, Paul and Mostafazadeh Davani, Aida and Calabrese, Agostina},
  booktitle = "Proceedings of the 8th Workshop on Online Abuse and Harms (WOAH 2024)",
  month = jun,
  year = "2024",
  address = "Mexico City, Mexico",
  publisher = "Association for Computational Linguistics",
  url = "https://aclanthology.org/2024.woah-1.19/",
  doi = "10.18653/v1/2024.woah-1.19",
  pages = "244--255"
}

@inproceedings{DBLP:conf/ecir/BevendorffCCDEFFKMMPPRRSSSTUWZ24,
  author = {Janek Bevendorff and Xavier Bonet Casals and Berta Chulvi and Daryna Dementieva and Ashaf Elnagar and Dayne Freitag and Maik Fr{"{o}}be and Damir Korencic and Maximilian Mayerl and Animesh Mukherjee and Alexander Panchenko and Martin Potthast and Francisco Rangel and Paolo Rosso and Alisa Smirnova and Efstathios Stamatatos and Benno Stein and Mariona Taul{'{e}} and Dmitry Ustalov and Matti Wiegmann and Eva Zangerle},
  editor = {Nazli Goharian and Nicola Tonellotto and Yulan He and Aldo Lipani and Graham McDonald and Craig Macdonald and Iadh Ounis},
  title = {Overview of {PAN} 2024: Multi-author Writing Style Analysis, Multilingual Text Detoxification, Oppositional Thinking Analysis, and Generative {AI} Authorship Verification - Extended Abstract},
  booktitle = {Advances in Information Retrieval - 46th European Conference on Information Retrieval, {ECIR} 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part {VI}},
  series = {Lecture Notes in Computer Science},
  volume = {14613},
  pages = {3--10},
  publisher = {Springer},
  year = {2024},
  url = {https://doi.org/10.1007/978-3-031-56072-9_1},
  doi = {10.1007/978-3-031-56072-9_1}
}