| language: | |
| - en | |
| tags: | |
| - sentiment-analysis | |
| # Sentiment Analysis in English | |
| ## bertweet-sentiment-analysis | |
| Repository: [https://github.com/finiteautomata/pysentimiento/](https://github.com/finiteautomata/pysentimiento/) | |
| Model trained with SemEval 2017 corpus (around ~40k tweets). Base model is [BERTweet](https://github.com/VinAIResearch/BERTweet), a RoBERTa model trained on English tweets. | |
| Uses `POS`, `NEG`, `NEU` labels. | |
| ## 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. | |
| 1. [TASS Dataset license](http://tass.sepln.org/tass_data/download.php) | |
| 2. [SEMEval 2017 Dataset license]() | |
| ## Citation | |
| If you use `pysentimiento` in your work, please cite [this paper](https://arxiv.org/abs/2106.09462) | |
| ``` | |
| @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} | |
| } | |
| ``` | |
| Enjoy! 🤗 | |