dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: string
- name: language
dtype: string
splits:
- name: train
num_bytes: 958500
num_examples: 5886
- name: test
num_bytes: 140808
num_examples: 857
download_size: 651241
dataset_size: 1099308
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
license: apache-2.0
task_categories:
- text-classification
language:
- es
tags:
- twitter
- SEPLN
- TASS
size_categories:
- 1K<n<10K
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
pretty_name: TASS Emotion Analysis
source_datasets:
- http://tass.sepln.org/2020/?page_id=74
Dataset Card for TASS Emotion Analysis
Dataset Details
Dataset Description
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.
- 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
- Languages: Spanish
- License: Apache-2.0
Dataset Sources
- Repository: TASS 2020
Dataset Composition
Data Fields
- text: Value(dtype='string') - The text of the tweet.
- label: Value(dtype='string') - The label representing the emotion expressed (e.g., anger, disgust, fear, joy, sadness, surprise, neutral).
- language: Value(dtype='string') - The language of the tweet (Spanish).
Data Splits
- train: 5886 examples
- test: 857 examples
Data Size
- Total size: 6743 examples across training and testing datasets.
Data Collection Process
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.
Uses
Intended Uses
The dataset is intended for training emotion classification systems, particularly in the context of social media and short text analysis.
Out-of-Scope Uses
Using the dataset for offensive or harmful purposes, misrepresenting the emotions analyzed, or manipulating the sentiments expressed in the tweets is discouraged.
Citation
BibTeX:
Not Provided
APA:
Not Provided
Dataset Authors
Not Provided
Dataset Contact
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