---
task_categories:
- text-classification
language:
- tl
- en
size_categories:
- 10K<n<100K
license: cc-by-4.0
---

# Dataset Card for 2016 and 2022 Hate Speech in Filipino

## Dataset Description

- **Homepage:** 
- **Repository:** 
- **Paper:** 
- **Leaderboard:** 
- **Point of Contact:** 

### Dataset Summary

Contains a total of 27,383 tweets that are labeled as hate speech (1) or non-hate speech (0). Split into 80-10-10 (train-validation-test) with a total of 21,773 tweets for training, 2,800 tweets for validation, and 2,810 tweets for testing.
Created by combining [hate_speech_filipino](https://huggingface.co/datasets/hate_speech_filipino) and a newly crawled 2022 Philippine Presidential Elections-related Tweets Hate Speech Dataset.

This dataset has an almost balanced number of hate and non-hate tweets:

```
Training Dataset:
Hate (1): 10,994
Non-hate (0): 10,779

Validation Dataset:
Hate (1): 1,415
Non-hate (0): 1,385

Testing Dataset:
Hate (1): 1,398
Non-hate (0): 1,412
```

Feel free to connect via [LinkedIn](https://www.linkedin.com/in/map-soriano/) for further information on this dataset or on the study that it was used on.

<!-- ### Supported Tasks and Leaderboards

[More Information Needed] -->

### Languages

The dataset consists mainly of Filipino text, supplemented with a few English words commonly employed in the Filipino language, especially during the 2016 and 2022 Philippine National/Presidential Elections

## Dataset Structure

### Data Instances

Non-hate speech sample data:
```
{
  "text": "Yes to BBM at SARA para sa ikakaunlad ng pilipinas",
  "label": 0
}
```

Hate speech sample data:
```
{
  "text": "Kapal ng mukha moIkaw magwithdraw!!!!![USERNAME]Hindi pelikula ang magsilbi sa bayan!!! Tama na pagbabasa ng script!!! Kakampink stfu Isko kupal",
  "label": 1
}
```

<!-- ### Data Fields

[More Information Needed] -->

### Data Splits

This dataset was split into 80% training, 10% validation, 10% testing.

<!-- ## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed] -->

## Additional Information

### Dataset Curators

- Castro, D.
- Dizon, L. J.
- Sarip, A. J.
- Soriano, M. A.

<!-- ### Licensing Information

[More Information Needed] -->

### Citation Information

**Research Title:** Application of BERT in Detecting Online Hate

**Published:** 2023

**Authors:** 
- Castro, D.
- Dizon, L. J.
- Sarip, A. J.
- Soriano, M. A.

Feel free to connect via [LinkedIn](https://www.linkedin.com/in/map-soriano/) for further information on this dataset or on the study that it was used on.

<!-- ### Contributions

[More Information Needed] -->