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goemotions

  • Description:

The GoEmotions dataset contains 58k carefully curated Reddit comments labeled for 27 emotion categories or Neutral. The emotion categories are admiration, amusement, anger, annoyance, approval, caring, confusion, curiosity, desire, disappointment, disapproval, disgust, embarrassment, excitement, fear, gratitude, grief, joy, love, nervousness, optimism, pride, realization, relief, remorse, sadness, surprise.

Split Examples
'test' 5,427
'train' 43,410
'validation' 5,426
  • Feature structure:
FeaturesDict({
    'admiration': tf.bool,
    'amusement': tf.bool,
    'anger': tf.bool,
    'annoyance': tf.bool,
    'approval': tf.bool,
    'caring': tf.bool,
    'comment_text': Text(shape=(), dtype=tf.string),
    'confusion': tf.bool,
    'curiosity': tf.bool,
    'desire': tf.bool,
    'disappointment': tf.bool,
    'disapproval': tf.bool,
    'disgust': tf.bool,
    'embarrassment': tf.bool,
    'excitement': tf.bool,
    'fear': tf.bool,
    'gratitude': tf.bool,
    'grief': tf.bool,
    'joy': tf.bool,
    'love': tf.bool,
    'nervousness': tf.bool,
    'neutral': tf.bool,
    'optimism': tf.bool,
    'pride': tf.bool,
    'realization': tf.bool,
    'relief': tf.bool,
    'remorse': tf.bool,
    'sadness': tf.bool,
    'surprise': tf.bool,
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
admiration Tensor tf.bool
amusement Tensor tf.bool
anger Tensor tf.bool
annoyance Tensor tf.bool
approval Tensor tf.bool
caring Tensor tf.bool
comment_text Text tf.string
confusion Tensor tf.bool
curiosity Tensor tf.bool
desire Tensor tf.bool
disappointment Tensor tf.bool
disapproval Tensor tf.bool
disgust Tensor tf.bool
embarrassment Tensor tf.bool
excitement Tensor tf.bool
fear Tensor tf.bool
gratitude Tensor tf.bool
grief Tensor tf.bool
joy Tensor tf.bool
love Tensor tf.bool
nervousness Tensor tf.bool
neutral Tensor tf.bool
optimism Tensor tf.bool
pride Tensor tf.bool
realization Tensor tf.bool
relief Tensor tf.bool
remorse Tensor tf.bool
sadness Tensor tf.bool
surprise Tensor tf.bool
  • Citation:
@inproceedings{demszky-2020-goemotions,
    title = "{G}o{E}motions: A Dataset of Fine-Grained Emotions",
    author = "Demszky, Dorottya  and
      Movshovitz-Attias, Dana  and
      Ko, Jeongwoo  and
      Cowen, Alan  and
      Nemade, Gaurav  and
      Ravi, Sujith",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.acl-main.372",
    pages = "4040--4054",
}