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README.md
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language:
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- en
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---
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## PCL
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Someone uses __Patronizing and Condescending Language (PCL)__ when their use of the language denotes a superior attitude towards someone else, or depicts them in a compassionate way, raising a feeling of pity among the audience.
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## pcl-roberta-base model for PCL detection
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This model is trained on __Don't Patronize Me!__ , a dataset of paragraphs extracted from media articles about vulnerable communities, published in 20 English-speaking countries or areas. The paragraphs have been manually annotated to assess if they contain any type of PCL.
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This is the PCL detection model built on roBERTa-base.
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- Git Repo: [Don't Patronize Me! official repository](https://github.com/Perez-AlmendrosC/dontpatronizeme)
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- Dataset: [Available upon request here] (https://docs.google.com/forms/d/e/1FAIpQLSe5KyzXgpnEOjS-Y6Gb8TTKiWxh4_qLuPL-NGiqKCyF41ALlg/viewform)
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<b>Labels</b>:
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0 -> Negative;
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1 -> Positive
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## Example Pipeline
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## Full classification example
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## Output:
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To know more about our work on PCL detection, the PCL detection model and the dataset, please refer to:
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## Reference Papers:
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```
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@inproceedings{perez2020don,
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title={Don’t Patronize Me! An Annotated Dataset with Patronizing and Condescending Language towards Vulnerable Communities},
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author={P{\'e}rez-Almendros, Carla and Anke, Luis Espinosa and Schockaert, Steven},
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booktitle={Proceedings of the 28th International Conference on Computational Linguistics},
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pages={5891--5902},
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year={2020}
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}
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```
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```
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@inproceedings{perez2022semeval,
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title={SemEval-2022 task 4: Patronizing and condescending language detection},
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author={P{\'e}rez-Almendros, Carla and Anke, Luis Espinosa and Schockaert, Steven},
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booktitle={Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)},
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pages={298--307},
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year={2022}
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}
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```
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```
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@inproceedings{perez2022identifying,
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title={Identifying condescending language: A tale of two distinct phenomena?},
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author={Perez-Almendros, Carla and Schockaert, Steven},
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booktitle={Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)},
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pages={130--141},
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year={2022}
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}
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```
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