- 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.
Additional Documentation: Explore on Papers With Code
Homepage: https://github.com/google-research/google-research/tree/master/goemotions
Source code:
tfds.text.Goemotions
Versions:
0.1.0
(default): No release notes.
Download size:
4.19 MiB
Dataset size:
32.25 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'test' |
5,427 |
'train' |
43,410 |
'validation' |
5,426 |
- Feature structure:
FeaturesDict({
'admiration': bool,
'amusement': bool,
'anger': bool,
'annoyance': bool,
'approval': bool,
'caring': bool,
'comment_text': Text(shape=(), dtype=string),
'confusion': bool,
'curiosity': bool,
'desire': bool,
'disappointment': bool,
'disapproval': bool,
'disgust': bool,
'embarrassment': bool,
'excitement': bool,
'fear': bool,
'gratitude': bool,
'grief': bool,
'joy': bool,
'love': bool,
'nervousness': bool,
'neutral': bool,
'optimism': bool,
'pride': bool,
'realization': bool,
'relief': bool,
'remorse': bool,
'sadness': bool,
'surprise': bool,
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
admiration | Tensor | bool | ||
amusement | Tensor | bool | ||
anger | Tensor | bool | ||
annoyance | Tensor | bool | ||
approval | Tensor | bool | ||
caring | Tensor | bool | ||
comment_text | Text | string | ||
confusion | Tensor | bool | ||
curiosity | Tensor | bool | ||
desire | Tensor | bool | ||
disappointment | Tensor | bool | ||
disapproval | Tensor | bool | ||
disgust | Tensor | bool | ||
embarrassment | Tensor | bool | ||
excitement | Tensor | bool | ||
fear | Tensor | bool | ||
gratitude | Tensor | bool | ||
grief | Tensor | bool | ||
joy | Tensor | bool | ||
love | Tensor | bool | ||
nervousness | Tensor | bool | ||
neutral | Tensor | bool | ||
optimism | Tensor | bool | ||
pride | Tensor | bool | ||
realization | Tensor | bool | ||
relief | Tensor | bool | ||
remorse | Tensor | bool | ||
sadness | Tensor | bool | ||
surprise | Tensor | bool |
Supervised keys (See
as_supervised
doc):None
Figure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):
- 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",
}