Datasets:
File size: 3,177 Bytes
896f0d8 367de65 1a97216 367de65 188d28c 1a97216 367de65 896f0d8 367de65 0d37ec0 367de65 0d37ec0 367de65 1a97216 367de65 1a97216 367de65 1a97216 367de65 1a97216 367de65 0d37ec0 367de65 0d37ec0 367de65 0d37ec0 367de65 0d37ec0 367de65 e7fe55b 367de65 0d37ec0 367de65 0d37ec0 367de65 e7fe55b 367de65 896f0d8 0d37ec0 367de65 0d37ec0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 |
---
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] --> |