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Sentiment Analysis in Spanish

robertuito-sentiment-analysis

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

Model trained with TASS 2020 corpus (around ~5k tweets) of several dialects of Spanish. Base model is RoBERTuito, a RoBERTa model trained in Spanish tweets.

Uses POS, NEG, NEU labels.

Results

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

model emotion hate_speech irony sentiment
robertuito 0.560 ± 0.010 0.759 ± 0.007 0.739 ± 0.005 0.705 ± 0.003
roberta 0.527 ± 0.015 0.741 ± 0.012 0.721 ± 0.008 0.670 ± 0.006
bertin 0.524 ± 0.007 0.738 ± 0.007 0.713 ± 0.012 0.666 ± 0.005
beto_uncased 0.532 ± 0.012 0.727 ± 0.016 0.701 ± 0.007 0.651 ± 0.006
beto_cased 0.516 ± 0.012 0.724 ± 0.012 0.705 ± 0.009 0.662 ± 0.005
mbert_uncased 0.493 ± 0.010 0.718 ± 0.011 0.681 ± 0.010 0.617 ± 0.003
biGRU 0.264 ± 0.007 0.592 ± 0.018 0.631 ± 0.011 0.585 ± 0.011

Note that for Hate Speech, these are the results for Semeval 2019, Task 5 Subtask B

Citation

If you use this model in your research, please cite pysentimiento and RoBERTuito 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}
}
@misc{perez2021robertuito,
      title={RoBERTuito: a pre-trained language model for social media text in Spanish},
      author={Juan Manuel Pérez and Damián A. Furman and Laura Alonso Alemany and Franco Luque},
      year={2021},
      eprint={2111.09453},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
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