pysentimiento / bertweet-irony

Irony detection in English

bertweet-irony

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

Model trained with SemEval 2018 dataset Task 3 (Van Hee et all, 2018) for irony detection. Base model is [BERTweet], a RoBERTa model trained in English tweets.

The positive class marks irony, the negative class marks not ironic content.

Results

Results for the four tasks evaluated in pysentimiento . Results are expressed as Macro F1 scores

Note that for Hate Speech, these are the results for Semeval 2019, Task 5 Subtask B (HS+TR+AG detection)

Citation

If you use this model in your research, please cite pysentimiento, dataset and pre-trained model 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{van2018semeval,
  title={Semeval-2018 task 3: Irony detection in english tweets},
  author={Van Hee, Cynthia and Lefever, Els and Hoste, V{\'e}ronique},
  booktitle={Proceedings of The 12th International Workshop on Semantic Evaluation},
  pages={39--50},
  year={2018}
}

@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}
}