mapsoriano/2016_2022_hate_speech_filipino

Dataset Card for 2016 and 2022 Hate Speech in Filipino

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 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 for further information on this dataset or on the study that it was used on.

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 Splits

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

Additional Information

Dataset Curators

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

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 for further information on this dataset or on the study that it was used on.