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--- |
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language: pt |
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widget: |
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- text: "Primeiro dia do novo emprego!" |
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--- |
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# Detection of employment status disclosures on Twitter |
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## Model main characteristics: |
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- class: Is Hired (1), else (0) |
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- country: BR |
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- language: Portuguese |
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- architecture: BERT base |
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## Model description |
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This model is a version of `neuralmind/bert-base-portuguese-cased` finetuned by [@manueltonneau](https://huggingface.co/manueltonneau) to recognize Portuguese tweets where a user mentions that she was hired in the past month. It was trained on Portuguese tweets from users based in Brazil. The task is framed as a binary classification problem with: |
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- the positive class referring to tweets mentioning that a user was recently hired (label=1) |
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- the negative class referring to all other tweets (label=0) |
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## Resources |
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The dataset of Portuguese tweets on which this classifier was trained is open-sourced [here](https://github.com/manueltonneau/twitter-unemployment). |
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Details on the performance can be found in our [ACL 2022 paper](https://arxiv.org/abs/2203.09178). |
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## Citation |
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If you find this model useful, please cite our paper: |
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``` |
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@inproceedings{tonneau-etal-2022-multilingual, |
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title = "Multilingual Detection of Personal Employment Status on {T}witter", |
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author = "Tonneau, Manuel and |
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Adjodah, Dhaval and |
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Palotti, Joao and |
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Grinberg, Nir and |
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Fraiberger, Samuel", |
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booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", |
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month = may, |
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year = "2022", |
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address = "Dublin, Ireland", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2022.acl-long.453", |
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doi = "10.18653/v1/2022.acl-long.453", |
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pages = "6564--6587", |
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} |
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``` |