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---
language: es # <-- my language
widget:
- text: "Difunde a contactos: #trabajo: Cajeros Zona Taxqueña- Turnos fijos. Oaxaca"
---
# Detection of employment status disclosures on Twitter
## Model main characteristics:
- class: Job Offer (1), else (0)
- country: MX
- language: Spanish
- architecture: BERT base
## Model description
This model is a version of `dccuchile/bert-base-spanish-wwm-cased` finetuned by [@manueltonneau](https://huggingface.co/manueltonneau) to recognize Spanish tweets containing job offers. It was trained on Spanish tweets from users based in Mexico. The task is framed as a binary classification problem with:
- the positive class referring to tweets containing job offers (label=1)
- the negative class referring to all other tweets (label=0)
## Resources
The dataset of Spanish tweets on which this classifier was trained is open-sourced [here](https://github.com/manueltonneau/twitter-unemployment).
Details on the performance can be found in our [ACL 2022 paper](https://arxiv.org/abs/2203.09178).
## Citation
If you find this model useful, please cite our paper:
```
@inproceedings{tonneau-etal-2022-multilingual,
title = "Multilingual Detection of Personal Employment Status on {T}witter",
author = "Tonneau, Manuel and
Adjodah, Dhaval and
Palotti, Joao and
Grinberg, Nir and
Fraiberger, Samuel",
booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.acl-long.453",
doi = "10.18653/v1/2022.acl-long.453",
pages = "6564--6587",
}
``` |