| language: en | |
| license: apache-2.0 | |
| datasets: | |
| - hatexplain | |
| The model is used for classifying a text as **Hatespeech**, **Offensive**, or **Normal**. The model is trained using data from Gab and Twitter and *Human Rationales* were included as part of the training data to boost the performance. | |
| The dataset and models are available here: https://github.com/punyajoy/HateXplain | |
| **For more details about our paper** | |
| Binny Mathew, Punyajoy Saha, Seid Muhie Yimam, Chris Biemann, Pawan Goyal, and Animesh Mukherjee "[HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection)". Accepted at AAAI 2021. | |
| ***Please cite our paper in any published work that uses any of these resources.*** | |
| ~~~ | |
| @article{mathew2020hatexplain, | |
| title={HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection}, | |
| author={Mathew, Binny and Saha, Punyajoy and Yimam, Seid Muhie and Biemann, Chris and Goyal, Pawan and Mukherjee, Animesh}, | |
| journal={arXiv preprint arXiv:2012.10289}, | |
| year={2020} | |
| } | |
| ~~~ | |