模型:

pysentimiento/bertweet-hate-speech

中文

Hate Speech detection in English

bertweet-hate-speech

Repository: https://github.com/pysentimiento/pysentimiento/

Model trained with SemEval 2019 Task 5: HatEval (SubTask B) corpus for Hate Speech detection in English. Base model is BERTweet , a RoBERTa model trained in English tweets.

It is a multi-classifier model, with the following classes:

  • HS : is it hate speech?
  • TR : is it targeted to a specific individual?
  • AG : is it aggressive?

License

pysentimiento is an open-source library for non-commercial use and scientific research purposes only. Please be aware that models are trained with third-party datasets and are subject to their respective licenses.

  • TASS Dataset license
  • SEMEval 2017 Dataset license
  • Citation

    If you use this model in your work, please cite the following papers:

    @misc{perez2021pysentimiento,
          title={pysentimiento: A Python Toolkit for Sentiment Analysis and SocialNLP tasks},
          author={Juan Manuel Pérez and Juan Carlos Giudici and Franco Luque},
          year={2021},
          eprint={2106.09462},
          archivePrefix={arXiv},
          primaryClass={cs.CL}
    }
    
    @inproceedings{nguyen2020bertweet,
      title={BERTweet: A pre-trained language model for English Tweets},
      author={Nguyen, Dat Quoc and Vu, Thanh and Nguyen, Anh Tuan},
      booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
      pages={9--14},
      year={2020}
    }
    
    @inproceedings{basile2019semeval,
      title={Semeval-2019 task 5: Multilingual detection of hate speech against immigrants and women in twitter},
      author={Basile, Valerio and Bosco, Cristina and Fersini, Elisabetta and Nozza, Debora and Patti, Viviana and Pardo, Francisco Manuel Rangel and Rosso, Paolo and Sanguinetti, Manuela},
      booktitle={Proceedings of the 13th international workshop on semantic evaluation},
      pages={54--63},
      year={2019}
    }
    

    Enjoy! ?