| ---
|
| dataset_info:
|
| - config_name: simplified_ekman
|
| features:
|
| - name: ru_text
|
| dtype: string
|
| - name: text
|
| dtype: string
|
| - name: labels
|
| dtype:
|
| list:
|
| class_label:
|
| names:
|
| - 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
|
| - neutral
|
| - name: labels_ekman
|
| dtype:
|
| list:
|
| class_label:
|
| names:
|
| - anger
|
| - disgust
|
| - fear
|
| - joy
|
| - sadness
|
| - surprise
|
| - neutral
|
| - name: id
|
| dtype: string
|
| splits:
|
| - name: train
|
| num_bytes: 10670621
|
| num_examples: 43410
|
| - name: validation
|
| num_bytes: 1330969
|
| num_examples: 5426
|
| - name: test
|
| num_bytes: 1323849
|
| num_examples: 5427
|
| download_size: 7683063
|
| dataset_size: 13325439
|
| 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-*
|
| license: apache-2.0
|
| task_categories:
|
| - text-classification
|
| language:
|
| - ru
|
| - en
|
| ---
|
|
|
| # Russian GoEmotions dataset
|
|
|
| The original dataset: [GoEmotions](https://huggingface.co/datasets/google-research-datasets/go_emotions) ([paper](https://aclanthology.org/2020.acl-main.372/)).
|
|
|
| The derived dataset was machine translated from English into Russian using the free Google Translate API (with [deep-translator](https://pypi.org/project/deep-translator/)). The translation script:
|
|
|
|
|
| ```python
|
| from datasets import load_dataset
|
| from deep_translator import GoogleTranslator
|
| from deep_translator.exceptions import TranslationNotFound
|
|
|
| original_dataset = load_dataset("go_emotions", name="simplified")
|
| translator = GoogleTranslator(source="en", target="ru")
|
|
|
| def translate_batch(batch):
|
| original_text = batch["text"]
|
|
|
| while True:
|
| try:
|
| translated_batch = translator.translate_batch(original_text)
|
| break
|
| except TranslationNotFound:
|
| print(f"Translation failed. Retrying...")
|
|
|
| # We fix untranslated entries (None values) by replacing them with the original text
|
| for i in range(len(translated_batch)):
|
| if not translated_batch[i]:
|
| translated_batch[i] = original_text[i]
|
| print(f"Replaced {original_text[i]} vs {translated_batch[i]}")
|
|
|
| batch["ru_text"] = translated_batch
|
|
|
| return batch
|
|
|
| translated_dataset = original_dataset.map(
|
| translate_batch, batched=True, batch_size=500
|
| )
|
| ```
|
|
|
| The derived dataset uses two aligned tagsets:
|
|
|
| - The original 27 + `neutral` emotion labels (may contain more than one label per sample):
|
| ```yaml
|
| 0: admiration
|
| 1: amusement
|
| 2: anger
|
| 3: annoyance
|
| 4: approval
|
| 5: caring
|
| 6: confusion
|
| 7: curiosity
|
| 8: desire
|
| 9: disappointment
|
| 10: disapproval
|
| 11: disgust
|
| 12: embarrassment
|
| 13: excitement
|
| 14: fear
|
| 15: gratitude
|
| 16: grief
|
| 17: joy
|
| 18: love
|
| 19: nervousness
|
| 20: optimism
|
| 21: pride
|
| 22: realization
|
| 23: relief
|
| 24: remorse
|
| 25: sadness
|
| 26: surprise
|
| 27: neutral
|
| ```
|
|
|
| - The basic 6 + `neutral` emotion labels as per [Paul Ekman's theory](https://en.wikipedia.org/wiki/Emotion_classification) (may contain more than one label per sample):
|
| ```yaml
|
| 0: anger
|
| 1: disgust
|
| 2: fear
|
| 3: joy
|
| 4: sadness
|
| 5: surprise
|
| 6: neutral
|
| ```
|
|
|
| Mapping from the 27 fine-grained emotions to the 6 basic emotions:
|
|
|
| | GoEmotions | Ekman |
|
| |---|---|
|
| | admiration | joy |
|
| | amusement | joy |
|
| | anger | anger |
|
| | annoyance | anger |
|
| | approval | joy |
|
| | caring | joy |
|
| | confusion | surprise |
|
| | curiosity | surprise |
|
| | desire | joy |
|
| | disappointment | sadness |
|
| | disapproval | anger |
|
| | disgust | disgust |
|
| | embarrassment | sadness |
|
| | excitement | joy |
|
| | fear | fear |
|
| | gratitude | joy |
|
| | grief | sadness |
|
| | joy | joy |
|
| | love | joy |
|
| | nervousness | fear |
|
| | optimism | joy |
|
| | pride | joy |
|
| | realization | surprise |
|
| | relief | joy |
|
| | remorse | sadness |
|
| | sadness | sadness |
|
| | surprise | surprise |
|
|
|
| ## Acknowledgements
|
|
|
| This work was supported by the EU Recovery and Resilience Facility project [Language Technology Initiative](https://www.vti.lu.lv) (2.3.1.1.i.0/1/22/I/CFLA/002). |
