File size: 1,739 Bytes
f361fcb d52d258 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
---
language: pt # <-- my language
widget:
- text: "T么 desempregada!"
---
# Detection of employment status disclosures on Twitter
## Model main characteristics:
- class: Is Unemployed (1), else (0)
- country: BR
- language: Portuguese
- architecture: BERT base
## Model description
This model is a version of `neuralmind/bert-base-portuguese-cased` finetuned to recognize Portuguese tweets where a user mentions that she is currently unemployed. It was trained on Portuguese tweets from users based in Brazil. The task is framed as a binary classification problem with:
- the positive class referring to tweets mentioning that a user is currently unemployed (label=1)
- the negative class referring to all other tweets (label=0)
## Resources
The dataset of Portuguese 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",
}
```
|