---
license: mit
task_categories:
- text-classification
language:
- gn
- es
pretty_name: JOTAD
size_categories:
- 1K<n<10K
---
# Text-based afective computing
We collected a dataset of tweets primarily written in Guarani (and Jopara, a code-switching language that combines Guarani and Spanish) and annotated them for three widely-used dimensions in sentiment analysis: 
1. emotion recognition (https://huggingface.co/datasets/mmaguero/gn-emotion-recognition),  
2. humor detection (**this repo**, https://huggingface.co/datasets/mmaguero/gn-humor-detection), and
3. offensive language identification (https://huggingface.co/datasets/mmaguero/gn-offensive-language-identification).

The statistics for the Jopara afective analysis datasets and their splits for each proposed task:
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6193f446979eb76ec3cc5b89/vKw1k6v4ZGtsj8b1BgPYM.png)

## How cite?

```
@article{aguero-et-al2023multi-affect-low-langs-grn,
  title={Multidimensional Affective Analysis for Low-resource Languages: A Use Case with Guarani-Spanish Code-switching Language},
  author={Agüero-Torales, Marvin Matías, López-Herrera, Antonio Gabriel, and Vilares, David},
  journal={Cognitive Computation},
  year={2023},
  publisher={Springer},
  notes={https://link.springer.com/article/10.1007/s12559-023-10165-0#citeas}
}
```