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metadata
language:
  - en
license: apache-2.0
task_categories:
  - text-classification
dataset_info:
  - config_name: simplified_ekman
    features:
      - name: text
        dtype: string
      - name: labels
        dtype:
          class_label:
            names:
              '0': sadness
              '1': joy
              '2': love
              '3': anger
              '4': fear
              '5': surprise
      - name: labels_ekman
        dtype:
          class_label:
            names:
              '0': anger
              '1': disgust
              '2': fear
              '3': joy
              '4': sadness
              '5': surprise
    splits:
      - name: train
        num_bytes: 71995184.8176143
        num_examples: 333447
      - name: validation
        num_bytes: 8999425.091192849
        num_examples: 41681
      - name: test
        num_bytes: 8999425.091192849
        num_examples: 41681
    download_size: 55584192
    dataset_size: 89994035
configs:
  - config_name: simplified_ekman
    data_files:
      - split: train
        path: simplified_ekman/train-*
      - split: validation
        path: simplified_ekman/validation-*
      - split: test
        path: simplified_ekman/test-*

Twitter Emotions dataset

The original dataset: Emotions

The derived dataset contains an additional labels_ekman column that maps the original emotion classes to the Paul Ekman's classification.

The column labels contains the emotion classes of the original dataset:

0: sadness
1: joy
2: love - not distinguished in the Ekman's classification
3: anger
4: fear
5: surprise

The column labels_ekman contains the corresponding Ekman's emotion classes:

0: anger
1: disgust - omitted, since not used in the original dataset
2: fear
3: joy
4: sadness
5: surprise

The mapping from the original to the Ekman's classification is made as follows:

Original Ekman
sadness (0) sadness (4)
joy (1) joy (3)
love (2) joy (3)
anger (3) anger (0)
fear (4) fear (2)
surprise (5) surprise (5)

See also

https://huggingface.co/datasets/AiLab-IMCS-UL/go_emotions-en

Acknowledgements

This work was supported by the EU Recovery and Resilience Facility project Language Technology Initiative (2.3.1.1.i.0/1/22/I/CFLA/002).