---
dataset_info:
- config_name: simplified_ekman
  features:
  - name: lt_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: 7095238
    num_examples: 43410
  - name: validation
    num_bytes: 885284
    num_examples: 5426
  - name: test
    num_bytes: 882333
    num_examples: 5427
  download_size: 6057071
  dataset_size: 8862855
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:
- lt
- en
---

# Lithuanian 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 Lithuanian 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="lt")

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["lt_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).