README.md

---
configs:
- config_name: default
data_files:
- split: train_en
  path: "dataset/en/en_train.jsonl"
language:
  - en
  - ja
  - el
  - es
license:
  - other
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
task_categories:
  - text-classification
pretty_name: xtopic
---

# Dataset Card for "cardiffnlp/tweet_topic_multilingual"

## Dataset Description
- **Dataset:** X-Topic
- **Domain:** X (Twitter)
- **Number of Class:** 19


### Dataset Summary
This is the official repository of X-Topic ([Multilingual Topic Classification in X: Dataset and Analysis](https://arxiv.org/abs/2410.03075), EMNLP 2024), a topic classification dataset based on X (formerly Twitter), featuring 19 topic labels.

The classification task is multi-label, with tweets available in four languages: English, Japanese, Spanish, and Greek.

The dataset comprises 4,000 tweets (1,000 per language), collected between September 2021 and August 2022.

The dataset uses the same taxonomy as [TweetTopic](https://huggingface.co/datasets/cardiffnlp/tweet_topic_multi). 


## Dataset Structure

### Data Splits

The dataset includes the following splits:

- **en**: English
- **es**: Spanish
- **ja**: Japanese
- **gr**: Greek
- **en_2022**: English data from 2022 (TweetTopic)
- **mix**: Mixed-language data
- **mix_2022**: Mixed-language data including (TweetTopic) from 2022
- **Cross-validation splits:**
  - **en_cross_validation_0** to **en_cross_validation_4**: English cross-validation splits
  - **es_cross_validation_0** to **es_cross_validation_4**: Spanish cross-validation splits
  - **ja_cross_validation_0** to **ja_cross_validation_4**: Japanese cross-validation splits
  - **gr_cross_validation_0** to **gr_cross_validation_4**: Greek cross-validation splits


### Data Instances
An example of `train` looks as follows.

```python
{
  "id": 1470030676816797696,
  "text": "made a matcha latte, black tea and green juice until i break my fast at 1!! my body and skin are thanking me",
  "label": [0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  "label_name": ["Diaries & Daily Life", "Fitness & Health", "Food & Dining"],
  "label_name_flatten": "Diaries & Daily Life, Fitness & Health, Food & Dining"
}
```

### Labels
| <span style="font-weight:normal">0: arts_&_culture</span> | <span style="font-weight:normal">5: fashion_&_style</span> | <span style="font-weight:normal">10: learning_&_educational</span>  | <span style="font-weight:normal">15: science_&_technology</span>  |
|-----------------------------|---------------------|----------------------------|--------------------------|
| 1: business_&_entrepreneurs | 6: film_tv_&_video  | 11: music              	| 16: sports           	|
| 2: celebrity_&_pop_culture  | 7: fitness_&_health | 12: news_&_social_concern  | 17: travel_&_adventure   |
| 3: diaries_&_daily_life 	| 8: food_&_dining	| 13: other_hobbies      	| 18: youth_&_student_life |
| 4: family               	| 9: gaming       	| 14: relationships      	|                      	|

Annotation instructions for English can be found [here](https://docs.google.com/document/d/1IaIXZYof3iCLLxyBdu_koNmjy--zqsuOmxQ2vOxYd_g/edit?usp=sharing).



## Citation Information
**TBA**