task_categories:text-classification language:hi language:en license:cc-by-4.0 size_categories:10K<n<100K format:csv modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
license: cc-by-4.0
task_categories:
- text-classification
language:
- hi
- en
pretty_name: Targeted Hate Speech Against Religion
size_categories:
- 10K<n<100K
---
The dataset consists 11,549 YouTube comments in Hindi-English code-mixed language for targeted hate speech detection against religion. Binary and multi-class tagging of YouTube comments is used. 
The classification of YouTube comments addresses two subtasks: Subtask-1 (Binary classification): comments are labeled as antireligion or non-antireligion. Subtask-2 (Multi-class classification): comments are labeled on the major targeted religions such as Islam, Hinduism, and Christianity, with a ‘none’ class also provided.

For more information, refer this paper: Sharma, D., Singh, A., & Singh, V. K. (2024). THAR-Targeted Hate Speech Against Religion: A high-quality Hindi-English code-mixed Dataset with the Application of Deep Learning Models for Automatic Detection. ACM Transactions on Asian and Low-Resource Language Information Processing.
https://doi.org/10.1145/3653017