metadata

configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
dataset_info:
  features:
    - name: text
      dtype: string
    - name: label
      dtype: string
  splits:
    - name: train
      num_bytes: 4032669
      num_examples: 20050
  download_size: 2186950
  dataset_size: 4032669
task_categories:
  - text-classification
language:
  - ar
pretty_name: ExaAEC
size_categories:
  - 10K<n<100K
license: apache-2.0

Dataset Card for "ExaAEC: A New Multi-label Emotion Classification Corpus in Arabic Tweets"

Paper:

S. Sarbazi-Azad, A. Akbari and M. Khazeni, "ExaAEC: A New Multi-label Emotion Classification Corpus in Arabic Tweets," 2021 11th International Conference on Computer Engineering and Knowledge (ICCKE), Mashhad, Iran, Islamic Republic of, 2021, pp. 465-470, doi: 10.1109/ICCKE54056.2021.9721493. keywords: {Knowledge engineering;Deep learning;Emotion recognition;Social networking (online);Neural networks;Natural language processing;Data models;Emotion Corpus;Emotion Detection;Deep Learning;Arabic Tweets},