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--- |
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language: |
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- en |
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tags: |
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- emotion-analysis |
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--- |
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# Emotion Analysis in English |
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## bertweet-base-emotion-analysis |
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Repository: [https://github.com/finiteautomata/pysentimiento/](https://github.com/finiteautomata/pysentimiento/) |
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Model trained with EmoEvent corpus for Emotion detection in English. Base model is [BerTweet](https://huggingface.co/vinai/bertweet-base). |
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## License |
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`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. |
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1. [TASS Dataset license](http://tass.sepln.org/tass_data/download.php) |
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2. [SEMEval 2017 Dataset license]() |
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## Citation |
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If you use `pysentimiento` in your work, please cite [this paper](https://arxiv.org/abs/2106.09462) |
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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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``` |
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and also the dataset related paper |
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``` |
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@inproceedings{del2020emoevent, |
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title={EmoEvent: A multilingual emotion corpus based on different events}, |
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author={del Arco, Flor Miriam Plaza and Strapparava, Carlo and Lopez, L Alfonso Urena and Mart{\'\i}n-Valdivia, M Teresa}, |
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booktitle={Proceedings of the 12th Language Resources and Evaluation Conference}, |
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pages={1492--1498}, |
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year={2020} |
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} |
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``` |
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Enjoy! 🤗 |
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