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@@ -42,3 +42,66 @@ pretty_name: TASS Emotion Analysis
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  source_datasets:
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  - http://tass.sepln.org/2020/?page_id=74
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  source_datasets:
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  - http://tass.sepln.org/2020/?page_id=74
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  ---
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+ # Dataset Card for TASS Emotion Analysis
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+ ## Dataset Details
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+ ### Dataset Description
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+ The TASS Emotion Analysis dataset aims to facilitate research in emotion classification from tweets written in Spanish. It contains labeled data categorized into Ekman’s six basic emotions along with a neutral category, based on events occurring in April 2019.
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+ - **Created by:** Manuel García Vega, Manuel Carlos Díaz Galiano, Miguel Ángel García Cumbreras, Flor Miriam Plaza del Arco, Arturo Montejo Ráez, Salud María Jiménez Zafra, Eugenio Martínez Cámara, César Antonio Aguilar, Edgar Casasola Murillo, Marco Antonio Sobrevilla Cabezudo, Luis Chiruzzo, Daniela A. Moctezuma
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+ - **Languages:** Spanish
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+ - **License:** [Apache-2.0](https://opensource.org/licenses/Apache-2.0)
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+ ### Dataset Sources
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+ - **Repository:** [TASS 2020](http://tass.sepln.org/2020/?page_id=74)
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+ ## Dataset Composition
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+ ### Data Fields
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+ - **text:** Value(dtype='string') - The text of the tweet.
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+ - **label:** Value(dtype='string') - The label representing the emotion expressed (e.g., anger, disgust, fear, joy, sadness, surprise, neutral).
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+ - **language:** Value(dtype='string') - The language of the tweet (Spanish).
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+ ### Data Splits
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+ - **train:** 5886 examples
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+ - **test:** 857 examples
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+ ### Data Size
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+ - **Total size:** 6743 examples across training and testing datasets.
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+ ### Data Collection Process
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+ The dataset was collected from tweets related to various events in April 2019, and it was curated to represent diverse Spanish dialects. Emojis and user mentions were replaced to ensure the focus remained on the textual content.
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+ ## Uses
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+ ### Intended Uses
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+ The dataset is intended for training emotion classification systems, particularly in the context of social media and short text analysis.
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+ ### Out-of-Scope Uses
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+ Using the dataset for offensive or harmful purposes, misrepresenting the emotions analyzed, or manipulating the sentiments expressed in the tweets is discouraged.
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+ ## Citation
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+ **BibTeX:**
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+ Not Provided
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+ **APA:**
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+ Not Provided
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+ ## Dataset Authors
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+ Not Provided
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+ ## Dataset Contact
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+ Not Provided