README.md

---
language: en        # <-- my language
widget:
 - text: "I was just hired, yay!"
---

# Detection of employment status disclosures on Twitter 

## Model main characteristics:
- class: Is Hired (1), else (0)
- country: US 
- language: English
- architecture: BERT base

## Model description 
This model is a version of `DeepPavlov/bert-base-cased-conversational` finetuned by [@manueltonneau](https://huggingface.co/manueltonneau) to recognize English tweets where a user mentions that she was hired in the past month. It was trained on English tweets from US-based users. The task is framed as a binary classification problem with:
- the positive class referring to tweets mentioning that a user was recently hired (label=1)
- the negative class referring to all other tweets (label=0)

## Resources

The dataset of English 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",
}
```