Datasets:
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---
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 (**this repo**, https://huggingface.co/datasets/mmaguero/gn-emotion-recognition),
2. humor detection (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:
## 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}
}
```
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