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# Sentiment Analysis in Spanish |
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## robertuito-sentiment-analysis |
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Repository: [https://github.com/pysentimiento/pysentimiento/](https://github.com/finiteautomata/pysentimiento/) |
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Model trained with TASS 2020 Task 2 corpus for Emotion detection in Spanish. Base model is [BETO](https://github.com/dccuchile/beto), a BERT model trained in Spanish. |
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Contains the six Ekman emotions plus a neutral class: |
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- anger |
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- disgust |
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- fear |
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- joy |
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- sadness |
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## Results |
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Results for the four tasks evaluated in `pysentimiento`. Results are expressed as Macro F1 scores |
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| model | emotion | hate_speech | irony | sentiment | |
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|:--------------|:--------------|:--------------|:--------------|:--------------| |
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| robertuito | 0.560 ± 0.010 | 0.759 ± 0.007 | 0.739 ± 0.005 | 0.705 ± 0.003 | |
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| roberta | 0.527 ± 0.015 | 0.741 ± 0.012 | 0.721 ± 0.008 | 0.670 ± 0.006 | |
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| bertin | 0.524 ± 0.007 | 0.738 ± 0.007 | 0.713 ± 0.012 | 0.666 ± 0.005 | |
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| beto_uncased | 0.532 ± 0.012 | 0.727 ± 0.016 | 0.701 ± 0.007 | 0.651 ± 0.006 | |
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| beto_cased | 0.516 ± 0.012 | 0.724 ± 0.012 | 0.705 ± 0.009 | 0.662 ± 0.005 | |
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| mbert_uncased | 0.493 ± 0.010 | 0.718 ± 0.011 | 0.681 ± 0.010 | 0.617 ± 0.003 | |
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| biGRU | 0.264 ± 0.007 | 0.592 ± 0.018 | 0.631 ± 0.011 | 0.585 ± 0.011 | |
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Note that for Hate Speech, these are the results for Semeval 2019, Task 5 Subtask B (HS+TR+AG detection) |
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## Citation |
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If you use this model in your research, please cite pysentimiento and RoBERTuito papers: |
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``` |
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@misc{perez2021pysentimiento, |
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title={pysentimiento: A Python Toolkit for Sentiment Analysis and SocialNLP tasks}, |
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author={Juan Manuel Pérez and Juan Carlos Giudici and Franco Luque}, |
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year={2021}, |
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eprint={2106.09462}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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@misc{perez2021robertuito, |
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title={RoBERTuito: a pre-trained language model for social media text in Spanish}, |
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author={Juan Manuel Pérez and Damián A. Furman and Laura Alonso Alemany and Franco Luque}, |
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year={2021}, |
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eprint={2111.09453}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |