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--- |
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license: mit |
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task_categories: |
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- text-classification |
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language: |
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- gn |
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- es |
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pretty_name: JOTAD |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Text-based afective computing |
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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: |
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1. emotion recognition (**this repo**, https://huggingface.co/datasets/mmaguero/gn-emotion-recognition), |
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2. humor detection (https://huggingface.co/datasets/mmaguero/gn-humor-detection), and |
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3. offensive language identification (https://huggingface.co/datasets/mmaguero/gn-offensive-language-identification). |
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|
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The statistics for the Jopara afective analysis datasets and their splits for each proposed task: |
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 |
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## How cite? |
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|
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``` |
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@article{aguero-et-al2023multi-affect-low-langs-grn, |
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title={Multidimensional Affective Analysis for Low-resource Languages: A Use Case with Guarani-Spanish Code-switching Language}, |
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author={Agüero-Torales, Marvin Matías, López-Herrera, Antonio Gabriel, and Vilares, David}, |
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journal={Cognitive Computation}, |
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year={2023}, |
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publisher={Springer}, |
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notes={https://link.springer.com/article/10.1007/s12559-023-10165-0#citeas} |
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} |
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``` |
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