metadata

dataset_info:
  features:
    - name: index
      dtype: int64
    - name: tweet
      dtype: string
    - name: class
      dtype: string
    - name: data
      dtype: string
    - name: moderator
      dtype: string
  splits:
    - name: train
      num_bytes: 34371418.55518156
      num_examples: 222196
    - name: test
      num_bytes: 3819132.4448184376
      num_examples: 24689
  download_size: 21373201
  dataset_size: 38190551
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*

Combined Dataset

This dataset contains tweets classified into various categories with an additional moderator label to indicate safety.

Features

tweet: The text of the tweet.
class: The category of the tweet (e.g., neutral, hatespeech, counterspeech).
data: Additional information about the tweet.
moderator: A label indicating if the tweet is safe or unsafe.

Usage

This dataset is intended for training models in text classification, hate speech detection, or sentiment analysis.

Licensing

This dataset is licensed under the MIT License.

Hatebase data set has been curated from multiple benchmark datasets and converted into binary class problem.

These are the following benchmark dataset: HateXplain : Converted hate,offensive, neither into binary Classification Peace Violence :Converted Peace and Violence, 4 classes into binary Classification Hate Offensive : Converted hate,offensive, neither into binary Classification OWS Go Emotion CallmeSexistBut.. : Binary classification along with toxicity score Slur : Based on slur, multiclass problem (DEG,NDEG,HOM, APPR) Stormfront : Whitesupermacist forum with Binary Classification UCberkley_HS : Multilclass hatespeech, counter hs or neutral (It has continuous score for eac class which is converted in our case) BIC (Each of 3 class has categorical score which is converted into binary using a threshold of 0.5) offensive, intent and lewd (sexual) -->

train example: 222196 test examples: 24689

Example

from datasets import load_dataset

dataset = load_dataset("your-hf-username/combined-dataset")
print(dataset['train'][0])